Behavioral and neural correlates of core-self and autobiographical-self processes

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Behavioral and neural correlates of core-self and autobiographical-self processes

Helder Filipe Cruz Araujo

Antonio Damasio, Advisor

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY

August 2014

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© 2013
Helder Filipe Cruz Araujo
All rights reserved.

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Acknowledgments

I would like to thank Dr. Antonio Damasio for the opportunity of working with
him. Doctors Antonio Damasio, Hanna Damasio, and Jonas Kaplan were very generous
mentors, who contributed profoundly to my research work and to my training as a
scientist. I am much obliged to them.
I am grateful to the members of my Dissertation Committee, Drs. Helena Chui
and Mary Helen Immordino-Yang, along with Drs. Antonio Damasio, Hanna Damasio,
as well as to Drs. Bosco Tjan, and Irving Biederman, members of my Advising
Committee, for their comments and suggestions.
I would like to express my gratitude to other members of the Brain Creativity
Institute. I shall start with my fellow graduate students for their support along my
graduate studies: Glenn Fox, Kingson Man, and Xiao-Fei Yang, with whom I worked so
closely during these years; Meghen, Andrea, Lei, Mona, Tong, Julie and Katy, former
BCI graduate students, and Panthea along with other new graduate students. In addition, I
would like to thank other members of the BCI, who have contributed to my research
work with their comments and suggestions during Lab meetings: Drs. Jessica, John, JC,
Lisa, and Mary Helen. More recently, Drs. Assal, Morteza, and Sarah have joined the
BCI, and have contributed to make of the Institute, such a great place to work.
I am grateful to the Neuroscience Graduate Program (NGP), including students
and professors, for their support and for the enriching experience of having contacted
with them. I am also grateful to professors outside of the NGP, in particular to Dr. Sharon
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Meyers for her teachings, and Dr. JoAnn Farver, for the experience of being a TA for one
of her courses.
I am much obliged to Dr. Maria de Sousa, a Portuguese Immunologist, whom I
met during third year of Medical School, and who has inspired me tremendously with her
vision of science. Dr. Maria de Sousa is also a co-founder and director of the Portuguese
Graduate Program in Areas of Basic and Applied Biology (GABBA), of which I have
been also a student. I am thankful to GABBA and the Portuguese Foundation for Science
and Technology (FCT) for a fellowship, which has supported me during a large part of
my graduate studies.
I would also like to thank the Neurology of Hospital S. João (HSJ), Porto,
Portugal, where up to 2007, I was a Neurology Resident, for their support. I am very
grateful to Dr. Carla Sofia Cardoso, School of Criminology of University of Porto,
Portugal, for her encouragement and support.
This work would not be possible without the help of so many others, such as the
administrative staff of the BCI, NGF, GABBA and HSJ.
Finally, I would like to thank my friends and family in Portugal for their support:
Ana, Carolina, Fred, Paula, Pedro Paulo, among other friends, and my grandmother. I
would like to thank my friends in Los Angeles, in particular, Ainsley, Gary, George, Jani
and Mollie, for their support.

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Table of Contents

List of Figures vii
List of Tables x
Abbreviations xiv
Abstract xv

General Introduction 1
The autobiographical self 1
The core self 5
Self-processes in the absence of an experimental task 6
References 8

Chapter 1. Cortical midline structures and autobiographical-self
processes: an activation-likelihood estimation (ALE) meta-analysis
11
Abstract 12
Introduction 13
Methods 16
Results 21
Discussion 32
References 37

Chapter 2.!Involvement of cortical midline structures in
autobiographical-self mental states
45
Abstract 46
Introduction 48
Methods 58
Results 63
Discussion 89
References 100

Chapter 3. Contrasting brain activity for core self and
autobiographical self mental states
108
Abstract 109
Introduction 111
Methods 118
Results 125
Discussion 159
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References 171

Chapter 4!.!Self-related states and brain activity during experimental
rest
177
Abstract 178
Introduction 180
Methods 190
Results 195
Discussion 241
References 248

General Discussion 253
References 258

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List of Figures
Figure 1.1 Meta-analysis of activation foci (159 foci; 21 experiments) for self-
traits compared with baseline
22
Figure 1.2 Meta-analysis of activation foci (114 foci; 12 experiments) for
other-traits compared with baseline
24
Figure 1.3 Meta-analysis of activation foci for self-traits compared with other-
traits in relation to both kinds of other (148 foci; 22 experiments), to
distant kinds of other (98 foci; 15 experiments) and to close kinds of
other (50 foci; 10 experiments)
27
Figure 1.4 Meta-analysis of activation foci for self-traits compared with other-
traits in relation to both kinds of other (148 foci; 22 experiments), to
distant kinds of other (98 foci; 15 experiments) and to close kinds of
other (50 foci; 10 experiments)
31

Figure 2.1 Experimental conditions used in the fMRI study 52
Figure 2.2 Summary of the co-variables investigated in the study 57
Figure 2.3 Reaction time (M and SEM) according to descriptiveness and
importance ratings

65
Figure 2.4 Conjunction analysis for the experimental conditions versus baseline 70
Figure 2.5 Other versus self 70
Figure 2.6 Facts versus traits 75
Figure 2.7 Self-traits versus self-facts 75

Figure 3.1 A. Experimental conditions used in the fMRI study. B. Between-
subject variables used in this study 115
Figure 3.2 Experimental conditions versus baseline
127
Figure 3.3 Interoception and exteroception compared with autobiographical-
self conditions. 131
Figure 3.4 Facts and traits compared with core-self conditions
135
Figure 3.5 Interoception versus exteroception
137
Figure 3.6 Facts versus traits
140
Figure 3.7 Parameter estimates for each condition in anterior CMSs
144
Figure 3.8 Parameter estimates for each condition in the superior PMC
145
Figure 3.9 Parameter estimates for each condition in superior PMC
146
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Figure 4.1 Variables explored in this study
185
Figure 4.2 DMN regions selected from previous literature
187
Figure 4.3 Anatomical masks regions for DMN regions of interest: cortical
midline structures, and hippocampal formation 187
Figure 4.4 Anatomical masks for regions involved in somatic processes: insula,
amygdala, precentral gyrus and postcentral gyrus 188
Figure 4.5 Default-mode network, determined by a probabilistic ICA (N = 37
participants). 203
Figure 4.6 Functional intrinsic connectivity in the left retrosplenial cortex and
estimated frequency of thoughts on body status during rest
204
Figure 4.7 Participants’ fcMRI in the left posterior cingulate cortex correlated
negatively with their estimated frequencies of thoughts about their
personality traits and biographic facts during rest.
205
Figure 4.8 Participants’ fcMRI in the left retrosplenial cortex, and temporal
parietal junction correlated negatively with their estimated
frequencies of thoughts about past events during rest 207
Figure 4.9 Participants’ fcMRI in the left and right hippocampal formation
correlated negatively with their estimated frequencies of thoughts
about present events during rest. 209
Figure 4.10 Participants’ fcMRI in the right precentral and postcentral gyri, and
left amygdala correlated negatively with their estimated frequencies
of thoughts about present events during rest. 210
Figure 4.11 Participants’ fcMRI in vMPFC correlated positively with their
estimated frequencies of thoughts about future events during rest.
211
Figure 4.12 Participants’ fcMRI in left and left anterior hippocampal formations,
and left temporal pole correlated negatively with their estimated
frequencies of thoughts about future events during rest. 212
Figure 4.13 Participants’ fcMRI in right postcentral gyrus correlated negatively
with their estimated frequencies of thoughts about future events
during rest. 213
Figure 4.14 Participants’ fcMRI in the dorsal medial prefrontal correlated
negatively with their PAC scores. 214
Figure 4.15 Participants’ fcMRI in the left insula correlated negatively with their
PAC scores. 214
Figure 4.16 Participants’ fcMRI in the left temporal parietal junction correlated
positively with their GFDD scores. 215
Figure 4.17 Participants’ fcMRI in the left precentral gyrus correlated positively
with their GFDD scores. 216
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Figure 4.18 Functional intrinsic connectivity in the left precentral gyrus, insula
and amygdala positively correlated with participants’ BAQ scores. 218
Figure 4.19 Participants’ fcMRI in the left PCC/ inferior PMC correlated
negatively with their Private SCS scores. 219
Figure 4.20 Participants’ fcMRI in the right insula correlated negatively with
their Private SCS scores. 220
Figure 4.21 Participants’ fcMRI in the left PCC /inferior PMC correlated
negatively with their Public SCS scores. 221
Figure 4.22 Participants’ fcMRI in the left PCC and precuneus correlated
negatively with their Anxiety SCS scores. 222
Figure 4.23 Participants’ fcMRI in the right postcentral gyrus correlated
negatively with their SCS scores. 223
Figure 4.24 Participants’ fcMRI in the ventromedial prefrontal cortex correlated
positively with their PD scores. 224

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List of Tables
Table 1.1 Individual experiments included in the meta-analysis
19
Table 1.2 Meta-analysis of activation foci for self-traits compared with
baseline (159 foci; 21 experiments)
23
Table 1.3 Meta-analysis of activation foci for other-traits compared with
baseline in relation both kinds of other (114 foci; 12 experiments),
distant others (46 foci; 6 experiments) and close others (68 foci; 9
experiments) 25
Table 1.4 Meta-analysis of activation foci for self-traits compared with
other-traits in relation to both kinds of other (148 foci; 22
experiments), to distant kinds of other (98 foci; 15 experiments)
and to close kinds of other (50 foci; 10 experiments) 31
Table 1.5 Meta-analysis of activation foci for other -traits compared with
self-traits in relation to both kinds of other combined (61 foci; 12
experiments), to distant kinds of other (23 foci; 7 experiments),
and to close kinds of other (38 foci; 6 experiments) 30

Table 2.1 Participants’ ratings and estimates collected after scanning
53
Table 2.2 Mean reaction times, ambivalence scores (ranging from 0 to 2),
importance ratings (ranging from 1 to 5) and memory estimates
(ranging from 1 to 5) for facts and traits relative to self and to
other
67

Table 2.3 Descriptiveness (1-5) and importance ratings (1-5) for negative
and for positive traits regarding self and other 68
Table 2.4 Participants’ mean scores for the personality measures used in this
study
68
Table 2.5 Task versus baseline
71
Table 2.6 Self versus other
73
Table 2.7 Self-facts versus self-traits 76
Table 2.8 Other-facts compared with other-traits 77
Table 2.9 Brain activity and descriptiveness ambivalence scores 79
Table 2.10 Brain activity and importance ratings for self-traits
80
Table 2.11 Brain activity and memory retrieval estimates ratings for self and
other
82
Table 2.12 Brain activity for self and participants’ Self-Consciousness scale
(SCS) scores 83
Table 2.13 Brain activity for self and participants’ Body Awareness
Questionnaire (BAQ) scores 85
Table 2.14 Brain activity for traits > facts and participants’ Body Awareness
Questionnaire (BAQ) scores 86
Table 2.15 Brain activity for other and participants’ Perspective Taking (PT)
scores
87
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Table 2.16 Brain activity for other and participants’ acquaintanceship
duration 88
Table 2.17 Brain activity for other-traits and participants’ descriptiveness
similarity scores. 89

Table 3.1 Mean reaction times, ambivalence scores (ranging from 0 to 2),
importance ratings (ranging from 1 to 5) for the conditions 126
Table 3.2 Activation peaks for the contrast interoception minus
autobiographical self (traits and facts). 128
Table 3.3 Activation peaks for the contrast exteroception minus
autobiographical self (traits and facts)
130
Table 3.4 Activation peaks for a conjunction analysis for exteroception
minus autobiographical self (traits and facts), and for interoception
minus autobiographical self. 132
Table 3.5 Activation peaks for facts minus core-self (interoception and
exteroception).
133
Table 3.6 Activation peaks for traits minus core-self
134
Table 3.7 Activation peaks for the conjunction of facts > coreself and traits
> coreself 136
Table 3.8 Activation peaks for interoception versus exteroception
138
Table 3.9 Activation peaks for facts versus traits.
140
Table 3.10 Activation peaks (and the corresponding contrasts) used for ROI
masks of CMSs 141
Table 3.11 Brain activity and participants’ importance estimates
147
Table 3.12 Brain activity for traits and participants’ descriptiveness
ambivalence scores. 148
Table 3.13 Brain activity for interoception and exteroception, and
participants’ descriptiveness ambivalence scores
149
Table 3.14 Brain activity and participants’ estimates of amount of memory
retrieved to answer questions for traits
150
Table 3.15 Brain activity and participants’ Body-awareness –questionnaire
(BAQ) scores
152
Table 3.16 Brain activity for traits and participants scores for the Awareness -
Body Perception Inventory (Awareness - BPI). 153
Table 3.17 Brain activity for core self > autobiographical self, and
participants Awareness -BPI.
154
Table 3.18 Brain activity and participants scores for the Autonomic Reaction
– BPI
155
Table 3.19 Brain activity and participants’ Autonomic Reaction – BPI scores
156
Table 3.20 Brain activity for autobiographical self > core self, and
participants Absorption – MIHT scores.
157
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Table 3.21 Brain activity, and participants’ Worry –MIHT.
158
Table 3.22 Brain activity yielded for traits, and participants’ scores for the
Worry – MIHT. 159

Table 4.1 DMN regions selected from previous literature
186
Table 4.2 Participants’ estimates of the frequency of thoughts during resting
scan. 195
Table 4.3 Participants’ mean and Standard Error Mean (SEM) for the
questionnaires used. 196
Table 4.4 Correlations between participants’ estimated frequencies of
thoughts during rest. 198
Table 4.5 Correlations between participants’ estimated frequencies of
thoughts, and scores for questionnaires 199
Table 4.6 Correlations between participants’ scores for the questionnaires
used 202
Table 4.7 Summary of the correlations in the DMN regions.
225
Table 4.8 Summary of the correlations in the somatic related regions
226
Table 4.9 Significance values for correlations between participants’
estimated frequencies of thoughts during rest corrected using
sequential Bonferroni correction 227
Table 4.10 Significance values for correlations found between participants’
tendency to daydream corrected using sequential Bonferroni
correction 228
Table 4.11 Significance values for correlations found between participants’
personality scores corrected using sequential Bonferroni
correction 229
Table 4.12 Models rendered by stepwise multiple regression of fcMRI in the
ventral MPFC on participants’ estimated frequencies of thoughts
about future events, BAQ and PD scores. 230
Table 4.13 Model rendered by stepwise multiple regression of fcMRI in the
vMPFC on participants’ estimated frequencies of thoughts about
future events, PCDD and BAQ scores 231
Table 4.14 Models rendered by stepwise multiple regression of fcMRI in the
PCC on participants’ estimated frequencies of thoughts regarding
their going body status events, Private-SCS scores, and Anxiety –
SCS scores 232
Table 4.15 Model rendered by stepwise multiple regression of fcMRI in the
PCC on participants’ estimated frequencies of thoughts regarding
their ongoing body status, and Public-SCS scores 232
Table 4.16 Models rendered by stepwise multiple regression of fcMRI in the
PCC on participants’ estimated frequencies of thoughts regarding
their traits and facts, Private-SCS scores, and Anxiety – SCS 233
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scores
Table 4.17 Model rendered by stepwise multiple regression of fcMRI in in the
left retrosplenium and participants’ estimated frequencies of
thoughts regarding their ongoing body status, and estimated
frequencies of thoughts regarding present events. 234
Table 4.18 Model rendered by stepwise multiple regression of fcMRI in the
temporal parietal junction on participants’ estimated frequencies
of thoughts regarding past events, and PCDD scores 235
Table 4.19 Model rendered by multiple regression of fcMRI in the right
hippocampus on participants’ estimated frequencies of thoughts
regarding their one’s body ongoing body status, and estimated
frequencies of thoughts regarding present events 236
Table 4.20 Model rendered by multiple regression of fcMRI in the right
hippocampus, on participants’ estimated frequencies of thoughts
regarding their body ongoing body status, and estimated
frequencies of thoughts regarding future events 236
Table 4.21 Model rendered by multiple regression of fcMRI in the left insula
on participants’ BAQ and PAC scores 237
Table 4.22 Model rendered by multiple regression of fcMRI in the right
amygdala on participants’ BAQ, GFDD, and PD scores 238
Table 4.23 Models rendered by stepwise multiple regression of fcMRI in the
right amygdala on participants’ estimated frequencies of thoughts
regarding present events (“thoughts about present”, for short), and
GFDD scores. 238
Table 4.24 Model rendered by multiple regression of fcMRI in the right
precentral gyrus on participants’ estimated frequencies of thoughts
regarding present events, and GFDD scores 239
Table 4.25 Model rendered by multiple regression of fcMRI in the left
postcentral gyrus on participants’ estimated frequencies of
thoughts regarding future events, Anxiety-SCS scores, and Private
SCS scores. 240
Table 4.26 Model rendered by multiple regression of fcMRI the right
postcentral gyrus on participants’ estimated frequencies of
thoughts about future event, and Anxiety-SCS scores. 240
Table 4.27 Model rendered by multiple regression of fcMRI the right
postcentral gyrus on participants’ estimated frequencies of
thoughts regarding past events, and Anxiety-SCS scores 241
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Abbreviations
BAQ Body awareness questionnaire
BPI Body Perception Inventory
CMS Cortical midline structures
DMN Default Mode Network
EC Empathetic concern scale
fcMRI Functional intrinsic connectivity
M Mean
MIHT Multidimensional Inventory of Hypochondria Traits
MPFC Medial prefrontal cortex
PCC Posterior cingulate cortex
PMC Posteromedial cortex
PT Perspective taking scale
RT Reaction times
SCS Self consciousness scale
SEM Standard error mean
VIF Variance inflation factor

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Abstract
At a given conscious moment, an individuals’ mind may be allocated to states
focusing on self-related processes. Those states tend to involve retrieving and processing
historical aspects of oneself, such as memories for events and facts pertaining to one’s
autobiography (states that have been designated as “autobiographical self”, Damasio,
1998), or examining one’s ongoing body status, such as sensations pertaining to one’s
internal milieu (states that have been designated as “core self”, Damasio, 1998).
In addition, self-related mental states may be elicited by specific stimuli directing
an individual to process certain self-related information, such as questions used as stimuli
in research studies; on the other hand, those states may occur in an apparently
spontaneous and unrestricted manner, such as during experimental rest when one’s mind
may wander through self-related thoughts.
This dissertation comprises behavior and fMRI studies that I conducted to
investigate the neural basis for autobiographical self and core self states. Chapter 1 and 2
report studies aimed at investigating autobiographical self states, including how these
states differ from those focusing on processing biographical information that pertains to
another person. Chapter 3 reports studies comparing autobiographical self and core self
states. Chapter 4 describes studies focusing on states that are not contingent on an
experimental task (i.e., experimental rest).
The results suggest that the extent and degree of the differences between self and
other in relation to processing biographical information vary depending on the domain of
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information in question, on who the other is in relation to self, and on personality
differences in relation to how one tends to process information pertaining to other.
Moreover, the neural bases for a given self-related mental state seem to depend on
the specific representations being involved in that state. Moreover, those states tend to be
rather complex. The data suggest that self-states that are driven by a requirement to
answer a particular question engage not only brain regions functionally dedicated to the
information targeted by the question but also brain regions that would not be presumably
necessary to answer the questions. Those states are also supported by hubs in the brain
connectivity (e.g., cortical midline structures), which possibly orchestrate the processing
of varied representations involved in those states. The results indicate also that self-
related mental states that occur in the absence of an experimental task (e.g., experimental
rest) may relate to functional intrinsic connectivity in regions of the so-called default
mode network as well as in body-related regions.

Reference
Damasio, A. R. (1998). Investigating the biology of consciousness. Philosophical
Transactions of the Royal Society of London. Series B, Biological Sciences,
353(1377), 1879–1882. doi:10.1098/rstb.1998.0339

General Introduction

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At a given conscious moment, an individual’s mind may be allocated to states
focusing on self-related processes. Those states tend to involve retrieving and processing
historical aspects of oneself, such as memories for events and facts pertaining to one’s
autobiography, or examining one’s ongoing body status, such as sensations pertaining to
one’s internal milieu.
In addition, self-related mental states may be elicited by a specific stimulus that
direct an individual to process certain self-related information, such as questions used as
stimuli in research studies; on the other hand, they may occur in an apparently
spontaneous and unrestricted manner, such as during experimental rest when one’s mind
may wander through self-related thoughts.

The autobiographical self
The term autobiographical self has been used to designate mental states that
derive from assembling fragmentary knowledge about facts and events defining an
individual’s biography. The assembly depends on momentary retrieval and display of
memories. Such memories are constructed over a lifetime of personal experiences, and
are stored in a coded, non-explicit manner and remain dormant; they can, however, be
reactivated as needed, more or less easily, depending on the value and strength of the
original experience and the frequency with which they are retrieved. Once displayed,
memories are treated as perceptual objects and may trigger emotional reactions and
retrieval of related memories. Consequently, the process of assembling memory
fragments may be simple, as when one displays landmark facts relative to one’s date and
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place of birth, or it may assume a complex structure, as when one is asked to describe a
specific event or period of one’s life (Damasio, 1998; Gallagher, 1999).
The investigation of behavioral and neural correlates of the autobiographical self
has focused largely on comparing the evaluation of one’s own traits (self-traits) with that
of another person’s (other-traits). This research has led some authors to suggest that self,
compared with other, is associated with shorter reaction times and better recall
performance (i.e., self-referent effect Rogers, Kuiper, & Kirker, 1977), and with greater
activity in cortical midline structures (CMSs), namely the medial prefrontal (MPFC), and
posteromedial cortices (PMC) as reviewed in Northoff et al., 2006. Although informative,
these suggestions have been challenged by findings from behavioral (Symons & Johnson,
1997), and functional studies (Legrand & Ruby, 2009). As noted in reviews of individual
studies (Legrand & Ruby, 2009) and in recent meta-analyses (Northoff, 2011), CMSs
seem to be engaged by self and by other. For example, compared with baseline, both self-
traits (e.g., Schmitz & Johnson, 2006) and other-traits (e.g., Craik et al., 1999) were
associated with greater activity in CMSs. Moreover, the comparison of level of activity
between self-traits and other-traits has yielded conflicting results. In some studies, self-
traits > other-traits revealed greater activity in the MPFC and PMC (e.g., D'Argembeau et
al., 2008); however, in different studies, the reverse contrast, other-traits > self-traits
yielded also greater activity in the MPFC and PMC (e.g., Pfeifer, Lieberman, & Dapretto,
2007). In brief, these findings do not seem compatible with the hypothesis that CMSs are
specific to self, and suggest that the role of CMSs in processes of autobiographical self
and in the tasks used in the relevant studies needs to be further studied.
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In my hypothesis, autobiographical self processes depend on structures that are
endowed with convergence and divergence architecture (i.e., cascades of converging
feedforward projections from varied regions, and of diverging projections back to the
originating sites; Damasio, 1989; Meyer & Damasio, 2009), which assist in the retrieval
and assembly of memory fragments stored in non-explicit forms in varied cortices. CMSs
have such architecture (see Hagmann et al., 2008; Parvizi, van Hoesen, Buckwalter, &
Damasio, 2006), and therefore may be involved in autobiographical self processes, but
they are not specific to those processes. They can rather assist varied processes that
require comparable levels of integration, such as the mind-wandering (frequently
associated with experimental rest, as reviewed in Buckner, Andrews-Hanna, & Schacter,
2008), and processes that underlie the tasks of evaluating biographic information such as
personality traits: retrieving, assembling and displaying memories, and deciding based on
the content of the memories that are displayed. Moreover, because processes of memory
retrieval and decision are likely to be required both for self and for other, CMSs are
probably also involved in the evaluation of information that pertains to other.
Accordingly, brain activity generated for autobiographical self states elicited by
evaluative tasks probably depends on processes of memory retrieval and decision. Those
processes are likely, in turn, to depend on several factors, namely: (i) the domain of
information being evaluated (e.g., whether it is personality traits or factual information);
(ii) participants’ differences in relation to representations for the information being
evaluated (e.g., how important the information is to one’s self-image); (iii) participants’
differences in relation to personality measures regarding how self-related information is
processed (e.g., Self-Consciousness Scale Scheier & Carver, 2005).
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Likewise, brain activity yielded for equivalent tasks in relation to another person
(e.g., an acquaintance) is also likely to vary, depending on the following factors: (i) the
domain of information being evaluated (e.g., whether it is personality traits or factual
information); ii) participants’ differences in relation to representations for the information
being evaluated (e.g., how important the information is to their image of their
acquaintance); (iii) participants’ differences in relation to the acquaintanceship (e.g., how
close the participant and the acquaintance are); (iv) participants’ differences in relation to
personality measures regarding to how information pertain to other tends to be processed
(e.g., perspective taking).
Chapters 1 and 2 present studies aimed at testing the above hypotheses and related
predictions.

The core self
The term core self has been used to designate mental states that allow individuals
to form a conscious account of their ongoing body status (Damasio, 1998). The core self
relates to interoceptive body changes (e.g., hunger, fatigue, or well-being), and to certain
exteroceptive body changes (e.g., pressure exerted on one’s arm).
The neural substrates for core self states have not been fully elucidated, but the
insular cortices and CMSs figure prominently among the regions that are likely to
contribute to those states. Specifically, the insular cortices have been shown to be
involved in processing varied body sensations, especially those related to interoception
(Craig, 2002). There is also evidence suggesting that CMSs are capable of assisting a
wide range of internally oriented processes, including processes behind core self states.
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For example, it is has been shown that CMSs are highly connected to cortical and
subcortical regions involved in body-related processing (Hagmann et al., 2008; Parvizi et
al., 2006).
Nonetheless, existing studies indicate that insular cortices and CMSs may also
play a role in autobiographical self states. It has been shown that insular cortices may be
involved in memory retrieval (Singer, Critchley, & Preuschoff, 2009) and in evaluating
one’s personality traits (Modinos, Ormel, & Aleman, 2009). As noted above, there is also
substantial evidence that CMSs may assist autobiographical self states. Consequently, in
order to understand the role of the insular and midline cortices in self-related states, it is
important to investigate how the involvement of these regions varies for core self and for
autobiographical self.
As in the case of autobiographical self states, brain activity generated during core
self states is likely to depend on varied factors, such as the following: (i) the domain of
body sensation (e.g., whether pertains to interoception or to exteroception); (ii)
participants’ differences in relation to specific body sensation being processed (e.g., how
important is a given body sensation to an individual); (iii) participants’ personality
differences in relation to how body-related information tends to be processed (e.g., how
much an individual tends to examine body sensations).
Chapter 3 presents a study contrasting brain activity for autobiographical self and
core self states.

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Self-related states and brain activity during experimental rest
The investigation of neural basis for self-related processes has focused largely on
brain activity generated for experimental tasks that require individuals to process self-
related stimuli (e.g., questions about themselves), but it may benefit also from
considering brain activity in the absence of an experimental task (i.e., experimental rest).
The meaning of brain activity during experimental rest has not been established,
but it has been proposed that brain activity during rest relates with mental processes
during rest, such as mind wandering (Mason et al., 2007), which raises the possibility that
this activity relates also to self-related states occurring during rest (e.g., thoughts
regarding one’s ongoing body status).
An alternative proposal for the meaning of brain activity during rest states that
brain activity during rest relates to a default mode of anatomical and functional brain
networks (DMN; Raichle et al., 2001). In other words, brain activity during rest is
regarded as a privileged manner to assess the anatomical and functional organization of
an individual’s brain. Moreover, measures of that activity, such as functional intrinsic
connectivity (fcMRI), can be used as correlates of personality, and neurological and
psychiatric disease (Fox & Raichle, 2007). This raises the possibility that fcMRI relates
to personality differences pertaining to how an individual tends to process self-related
information.
Chapter 4 presents a study testing the above possibilities.

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References
Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The Brain's Default
Network: Anatomy, Function, and Relevance to Disease. Annals of the New York
Academy of Sciences, 1124(1), 1–38. doi:10.1196/annals.1440.011
Craig, A. D. (2002). How do you feel? Interoception: the sense of the physiological
condition of the body. Nature Reviews Neuroscience, 3(8), 655–666.
doi:10.1038/nrn894
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Chapter 1
Cortical midline structures and autobiographical-self processes: an activation-likelihood
estimation (ALE) meta-analysis

This chapter is, in full, a reprint of the material as it appears in: Araujo, H. F.,
Kaplan, J., & Damasio, A. (2013). Cortical midline structures and autobiographical-self
processes: an activation-likelihood estimation meta-analysis. Frontiers in Human
Neuroscience, 7. The dissertation author was the primary investigator and author of this
paper.

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Abstract
The autobiographical self refers to a mental state derived from the retrieval and
assembly of memories regarding one’s biography. The process of retrieval and assembly,
which can focus on biographical facts or personality traits or some combination thereof,
is likely to vary according to the domain chosen for an experiment. To date, the
investigation of the neural basis of this process has largely focused on the domain of
personality traits using paradigms that contrasted the evaluation of one’s traits (self-traits)
with those of another person’s (other-traits). This has led to the suggestion that cortical
midline structures (CMSs) are specifically related to self states. Here, with the goal of
testing this suggestion, we conducted activation-likelihood-estimation (ALE) meta-
analyses based on data from 28 neuroimaging studies. The ALE results show that both
self-traits and other-traits engage CMSs; however, the engagement of medial prefrontal
cortex (MPFC) is greater for self-traits than for other-traits, while the posteromedial
cortex (PMC) is more engaged for other-traits than for self-traits. These findings suggest
that the involvement CMSs is not specific to the evaluation of one’s own traits, but also
occurs during the evaluation of another person’s traits.

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Introduction
The autobiographical self can be described as a mental state deriving from a
momentary access to information regarding facts and events in one’s life (Damasio,
1998). The access depends on the retrieval and assembly of memories pertaining to a
multitude of facts and events and is likely to vary with the kinds of memories involved.
Access may focus on retrieval of relatively simple memory representations, as when one
retrieves information regarding demographic aspects of one’s identity (e.g., one’s
nationality); or it may be more specific and involve retrieval of representations of
perceptual and emotional aspects of a particular episode (e.g., one’s college graduation).
The effort needed for the retrieval is likely to vary as well and it is probably smaller for
memories pertaining to prominent aspects of one’s biography than for memories
regarding more remote events. Once memories are displayed, they may trigger a varied
amount of related memories and the associated emotional responses. In brief, the nature
and scope of the knowledge exhibited in an autobiographical-self state varies according
to the domains of information that are recruited.
The investigation of the behavioral and neural correlates of the autobiographical
self has explored varied domains, including one’s own name (e.g., Tacikowski et al.,
2011) , voice (e.g., Nakamura et al., 2001), body parts (e.g., Platek et al., 2008), and
personality traits (e.g., Kelley et al., 2002 ) and autobiographical memories (e.g., Cabeza
& St Jacques, 2007). Here, we focus on the domain of personality traits. By contrasting
self-traits (i.e., deciding if a given personality trait accurately describes oneself) with
other-traits (i.e., deciding if a given personality trait accurately describes another person),
some studies have found an advantage of self-traits over other-traits in terms of reaction
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times and memory performance. This has led to the suggestion that information
pertaining to self is processed differently from information pertaining to another person,
and has become known as the “self-referent effect” (Rogers et al., 1977). Moreover, it has
led to the idea that the neural basis of self-reference involves cortical midline structures
(CMSs), namely the medial prefrontal (MPFC), anterior cingulate (ACC), and
posteromedial (PMC) cortices (reviewed in Northoff et al., 2006). The results of the
existing studies are not conclusive, however, in regard to the existence of the self-referent
effect (e.g., Symons and Johnson, 1997) as well as in regard to the association of CMSs
with self-reference (e.g., Legrand and Ruby, 2009).
With the development of techniques capable of performing meta-analysis of
neuroimaging data, some attempts have been made to investigate consistent differences
between self and other in terms of brain activity (Denny et al., 2012; Northoff et al.,
2006; Qin and Northoff, 2011; Qin et al., 2011). Although informative, the studies
included in these meta-analyses varied in terms of the self-referential stimuli used
(comprising, for example, autobiographical and episodic memories, personality traits, the
participants’ faces or other body parts, and the participants’ names), as well as in terms of
the tasks performed (including, for example, tasks in which the participants were not
given any specific instructions other than to look at or to listen to the stimuli; and tasks in
which the participants were asked to judge/evaluate or to reflect on aspects of the stimuli).
This heterogeneity of domains and approaches is a potential limitation given that
autobiographical-self processes are likely to vary according to the stimuli and the tasks
one uses (as discussed in Klein and Gangi, 2010). In addition, the kinds of “other” used
in the original study and the relationship between self and other are likely to be decisive
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15
in establishing differences between self and other. The differences between self and other
in terms of reaction times and memory performance have been shown to be reduced or
eliminated when the other is a close acquaintance, such as the participants’ close friends
(Symons and Johnson, 1997), or parents (Markus and Kitayama, 1991). In addition,
activation in CMSs seems to vary according to who the other is. For example, activity in
the MPFC during evaluation of traits for self is not different from that of a close other,
but happens to be greater for self than for a distant other (Ochsner et al., 2005).
Here, we conduct meta-analyses of the previously reported brain activations
restricted to the direct evaluation of personality traits pertaining to self (“self-traits”) and
to other (“other-traits”). We attempt to compare self and other in regard to processes
underlying equivalent tasks with equivalent stimuli. We also investigate how the contrast
of brain activity between self-traits and other-traits varied according to who the other is in
relation to self (distant others versus close others).
Our working assumption is that in order to evaluate when a given personality trait
describes one’s self accurately, one needs to retrieve and assemble memories (an
autobiographical-self state) and decide based on the knowledge accessed. These
processes are likely to depend on structures capable of high-levels of integration, such as
CMSs (Hagmann et al., 2008; Parvizi et al., 2006); they may also engage structures
involved in emotion-related somatic representations such as the insula because of the
subjective and emotional content of the personality traits (Damasio and Carvalho, 2013).
Furthermore, evaluating when a given personality trait describes another person requires
memory retrieval and decisions and is thus likely to involve similar brain structures.
Nonetheless, we predict differences between self and other in terms of brain activity.
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16
These differences are probably commensurate with the differences present in the
representations accessed during the evaluation. Representations regarding one’s self are
elaborated during a lifetime of episodes and events, whereas representations regarding
another person are probably elaborated via a more limited amount of interactions with
that person during the acquaintanceship. Thus the representations regarding one’s self are
probably more numerous and more easily retrieved than those regarding another person,
and it is also probable that emotion responses associated with the evaluation are greater
for self than for other. Finally, the differences between self and other may be greater
when the other is a distant other than when the other is a close other, someone with whom
one has a close relationship and interacts frequently over a long period of time.

Methods
Studies used
The studies included were found and retrieved via PubMed and PsychARTICLES,
using “self” as a search word for studies that used functional magnetic imaging (fMRI).
The citations within the retrieved publications were also explored as possible studies to
include in the meta-analysis. This initial search was concluded by November 31, 2012.
From the initial pool of retrieved publications, we selected only studies that investigated
the direct evaluation of the domain of personality traits regarding self (i.e., the
participants were asked to judge whether a set of personality traits described themselves),
other (i.e., the participants were asked to judge whether a set of personality traits
described another person), or both. We restricted the selection to studies that presented
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17
whole-brain analyses and included healthy subjects whose ages ranged from 18 to 50
years old.
The final selection assembled 28 publications, 31 studies (each study including a
different set of participants; Table 1.1). We categorized the kind of other used in the
experiments into two groups: (i) distant others, which included a well-known person
from the public domain (e.g., former US President George W Bush; or a distant
acquaintance of the subject (e.g., a classmate); (ii) close others, which included friends,
siblings or romantic partners, or the participants’ parents. Data regarding other-traits for
underrepresented categories of other (i.e., Harry Potter in Pfeifer et al., 2007, and historic
religious leaders in Han et al., 2010) were not included in the analysis.
The coordinates of the peaks of activation foci were recorded for each contrast in
each experiment. Foci referring to the same contrast of interest (e.g., other > baseline)
that derived from more than one experiment (e.g., distant other and the participant’s
mother) using the same group of participants, were analyzed together (for that contrast) in
order to minimize within-group effects (Turkeltaub et al., 2011). The total number of foci,
experiments and participants for each contrast were as follows: (i) self-traits > baseline,
159 foci, 21 experiments, 340 participants, in which the baseline was rest (ii) other -traits
> baseline, 114 foci, 12 experiments, 219 participants for both distant and close others;
46 foci, 6 experiments, 95 participants for distant others; and 68 foci, 9 experiments and
167 participants; (iii) self -traits > other-traits, 148 foci, 22 experiments, 383 participants
for both distant others and close others; 98 foci, 15 experiments, 259 participants for
distant others; 50 foci, 10 experiments, 185 participants for close others; (iv) other -traits
> self-traits, 61 foci, 12 experiments, 218 participants, for distant others and close others
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combined; 23 foci, 7 experiments, 127 participants, for distant others; 38 foci, 6
experiments, 107 participants, for close others.
The baseline included in the studies was either rest (3 experiments regarding self-
traits > baseline) or an active task involving some judgment of trait words, such as in
relation to the number of syllables of the words, the case or the font in which the words
were written, the valence of the words (17 experiments regarding self-traits > baseline;
and all the experiments regarding other-traits > baseline).
Data regarding the reaction times were also recorded; these data were available in
15 experiments: 9 referring to experiments that involved distant others, and 6 referring to
experiments that involved close others.

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Table 1. 1. Individual experiments included in the meta-analysis. The same study is listed
twice when it included two different populations.

Study Number
of
subjects
Self >
baseline
Other >
baseline
Self >
Other
Other >
Self
Benoit et al., 2010 16 1 1 1 1
D'Argembeau et al., 2007 17 0 0 1 0
D'Argembeau et al., 2010 20 1 1 0 0
Fossati et al., 2003 14 1 0 0 0
Gutchess et al., 2007 19 0 0 1 1
Han et al., 2010 14 1 0 1 0
Heatherton, 2006 30 1 1 1 1
Jenkins and Mitchell, 2011 15 0 0 1 1
Kelley et al., 2002 20 0 0 1 0
McAdams and Krawczyk,
2012
18
0 0 1 1
Modinos et al., 2009 16 0 0 1 1
Modinos et al., 2011 18 1 1 1 1
Murphy et al., 2010 10 1 1 0 1
Ochsner et al., 2005 17 1 1 0 0
Ochsner et al., 2005 16 0 0 2 2
Pfeifer et al., 2009 17 1 0 0 0
Pfeifer et al., 2007 17 1 0 0 0
Powell et al., 2009 28 0 0 1 1
Schmitz et al., 2004 19 1 1 1 0
Schmitz and Johnson,
2006)
15
1 0 0 0
van Buuren et al., 2010 19 1 0 0 0
Vanderwal et al., 2008 17 0 1 1 1
Wang et al., 2012 32 1 3 3 0
Whitfield-Gabrieli et al.,
2011
10
1 0 0 0
Yaoi et al., 2009 17 1 1 0 0
Yoshimura et al., 2009 15 1 1 1 1
Zhang et al., 2006 7 1 0 1 0
Zhang et al., 2006 7 1 0 1 0
Zhu et al., 2007 13 1 2 1 0
Zhu et al., 2007 13 1 2 2 0
Zhu et al., 2012 14 0 0 1 0
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Data analysis
A probabilistic map of activation was generated for each contrast of interest using
activation likelihood- estimate (ALE) with GingerALE2.3 (http://brainmap.org/ale/
index.html). The steps involved in this estimation are explained in detail in Turkeltaub et
al. (2011). For a given contrast, the ALE values represent the likelihood of observing
activity in that voxel for at least one group of participants (Turkeltaub et al., 2011). The
coordinates in Tailarach were transformed into MNI (SPM) using icbm2tal transform
(Laird et al., 2010; Lancaster and Gutiérrez, 2007). Two thresholds were applied to the
results: first, a threshold of p < .001 uncorrected; subsequently, a cluster size probability
threshold of p < 0.05 determined by permutations of random data (5000 permutations).
The ALE maps were compared between contrasts of interest using the ALE subtraction
analysis (random effects, Laird et al., 2005) available in the same software. This included
a permutation test (5,000 permutations) to determine the statistical significance of the
differences, and a threshold of p < .001 (uncorrected). All the results are in MNI
coordinates and were overlaid in a standard MNI brain (Colin27_T1_seg_MNI.nii) using
Mango (http://ric.uthscsa.edu/mango/) and MRIcroGL
(http://www.mccauslandcenter.sc.edu/mricrogl/).
The effect size for the difference in reaction time between self and other was
assessed using the reported t-test and F-test parameters, and calculating point-biserial
correlation r values, as suggested and explained in Rosenthal and DiMatteo, 2001. In
brief, the r values were calculated using the following formula: r = [(t
2
/(t
2
+df)]
1/2
, or r =
[(F
2
/(F
2
+df
error
)]
1/2
. Then, the r values were converted into Fisher Z values; mean Z
scores and corresponding 95% confidence interval were calculated for the experiments
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21
according to the kind of other (close others and distant others), and then transformed back
into r values.
Results
Reaction times
Reaction times (RTs) tended to be greater for other-traits than for self-traits. The
average unstandardized difference between mean RTs for other-traits and mean RTs for
self-traits was 24.53 milliseconds (SEM = 12.56 ms; mean RTs reported in 13
experiments). Statistically significant differences between self-traits and other-traits were
reported in 6 experiments (5 regarding distant others, and 1 regarding close kind of
other); in 5 of these experiments (4 referring to distant others and 1 referring to close
others), mean RTs were greater for other than for self.
The average unstandardized difference between mean RT for other-traits and
mean RT for self-traits was greater when addressing distant others (M = 32.93 ms; SEM
= 17.98 ms; N = 8 experiments) than when addressing close others (M = 11.10 ms; SEM
=15.9 ms; N = 5 experiments). The 95% confidence interval of the effect size r followed
the same trend: for distant others, it was 0.897 +/- 0.804 ms (N = 7 experiments); for
close others, it was 0.299 +/- 0.202 ms (N = 6 experiments).
Meta-analyses of brain activation
Self-traits versus baseline. The meta-analysis of activation foci for self-traits
yielded 8 clusters of significant activation likelihood (ALE): bilaterally in medial
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!
22
prefrontal cortex (MPFC), posteromedial cortex (PMC), and lateral prefrontal cortex, and
in the left insula and middle temporal gyrus (Table 1.2, Figure 1.1).

Figure 1.1. Meta-analysis of activation foci (159 foci; 21 experiments) for self-traits
compared with baseline.

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23
Table 1.2. Meta-analysis of activation foci for self-traits compared with baseline (159
foci; 21 experiments).
Cluster # Brain region x y z Volume
(mm
3
)
ALE
(x10
-3
)
1 L medial prefrontal cortex
-2 60 22 5152 33.97
2 L insula/ inferior frontal gyrus
-34 20 -12 3168 21.20
3 L posteromedial cortex
-4 -52 26 2304 17.77
4 L superior frontal gyrus
-8 36 50 1744 19.56
5 L middle temporal gyrus
-60 -4 -16 880 14.71
6 L supramarginal gyrus
-44 -54 28 808 21.09
7 R inferior frontal gyrus
48 26 -14 488 14.17
8 L middle temporal gyrus
-60 -36 2 440 14.65
9 L middle frontal gyrus
-42 8 48 440 14.96

Other-traits versus baseline. The meta-analysis of activation foci for other-traits
regarding distant and close kinds other yielded 8 clusters of significant ALE: bilaterally,
in the MPFC and PMC, in the left inferior frontal, middle temporal, and angular gyri, and
in the right orbitofrontal gyrus (Table 1.3, Figure 1.2). The same meta-analysis restricted
to distant others (i.e., a category that includes a well-know person of the public domain or
participants’ distant acquaintances such as classmates or housemates) revealed 24 clusters
of significant ALE: bilaterally in the PMC, MPFC, middle temporal and supramarginal
gyri, and in the left superior frontal gyrus and temporal pole, and in the right orbitofrontal
gyrus and cerebellum (Table 1.3). In addition, the same meta-analysis restricted to close
others (i.e., a category that includes a close acquaintance or relative of the participants,
such as the participants’ parents, or a participant’s best friend/ or sibling) yielded 6
clusters of significant ALE: bilaterally in the MPFC and PMC, and in the left superior
and inferior frontal gyri and middle temporal gyrus (Table 1.3).
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!
24

Figure 1.2. Meta-analysis of activation foci (114 foci; 12 experiments) for other-traits
compared with baseline.

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!
25
Table 1.3. Meta-analysis of activation foci for other-traits compared with baseline in
relation both kinds of other (114 foci; 12 experiments), distant others (46 foci; 6
experiments) and close others (68 foci; 9 experiments).
Cluster # Brain region x y z Volume
(mm
3
)
ALE
(x10
-3
)

Other-traits > baseline
Distant and close others
1
L superior frontal gyrus/ medial
prefrontal cortex -10 56 32 3544 16.10
2
L posteromedial cortex
-4 -54 28 3160 23.14
3
L superior frontal gyrus
-10 42 48 1632 20.20
4
L inferior frontal gyrus
-48 28 -8 976 15.67
5
L middle temporal gyrus
-60 -12 -14 968 13.18
6
L angular gyrus
-50 -66 28 616 10.60
7
L temporal pole
-44 10 -36 528 12.09
8
R orbitofrontal gyrus
6 58 -24 336 12.96

Distant others
1 L middle temporal gyrus -60 0 -26 1224 12.73
2
L medial prefrontal/ superior
frontal gyrus -6 60 28 696 10.90
3
L posteromedial cortex
-4 -56 30 632 10.18
4
R medial prefrontal cortex
2 46 -20 552 9.75
5
L temporal pole
-42 10 -38 448 10.68
6
L supramarginal gyrus
-48 -64 34 288 8.94
7
R temporal pole
48 12 -28 96 8.61
8
L temporal pole
-54 2 -38 64 8.05
9
L medial prefrontal cortex
-8 52 -2 56 8.17
10
L frontal pole/ medial
prefrontal cortex -2 64 4 56 8.17
11
R/L posteromedial cortex
0 -56 16 56 8.32
12
R cerebellum
32 -84 -32 48 7.77
13
R temporal pole/ middle
temporal gyrus 58 10 -26 48 7.49
14
R middle temporal gyrus
66 -4 -20 48 7.63
15
L superior frontal gyrus
-12 34 50 48 7.81
16
L superior frontal gyrus
-14 46 50 48 7.74
17
L temporal pole
-44 22 -42 40 7.44
18
L medial prefrontal cortex
-8 36 -20 40 7.82
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26
19
R posteromedial cortex
8 -42 30 40 7.73
20
L superior frontal gyrus
-10 54 42 40 8.00
21
R orbitofrontal cortex
6 58 -26 32 7.45
22
R middle temporal gyrus
58 -12 -20 32 7.38
23
R supramarginal gyrus
58 -58 16 32 7.52
24
R posteromedial cortex
12 -46 26 32 7.41

Close other
1
L superior frontal gyrus
-10 42 48 1424 20.20
2
L posteromedial cortex
-4 -54 28 1328 14.80
3
L inferior frontal gyrus
-48 28 -8 1136 15.67
4
L medial prefrontal cortex/
superior frontal gyrus -12 56 32 624 13.42
5
L middle temporal gyrus
-62 -30 -2 552 11.31
6
L medial prefrontal cortex/
superior frontal gyrus -2 58 18 352 10.16

Self-traits versus other-traits
Self-traits versus other-traits for both distant others and close others. In the
meta-analysis of the activation foci for self-traits > other-traits, we observed 4 clusters of
significant ALE: bilaterally, in the MPFC and anterior cingulate cortex (ACC), in the left
PMC, and in the right middle frontal gyrus. Table 1.4, Figure 1.3). The meta-analysis of
the activations relative to the reverse contrast (other-traits > self-traits) yielded 8 clusters
of significant ALE: bilaterally in the PMC and medial temporal gyrus, and in the right
basal forebrain, superior parietal lobule and cerebellum (Table 1.5, Figure 1.4).
Self-traits versus other-traits for distant others. The meta-analysis of the
activation foci for self –traits > other-traits regarding only distant others yielded 9
clusters of significant ALE, namely, bilaterally, in the MPFC, in the right superior frontal
gyrus, and in the left PMC, insula and angular gyrus (Table 1.4, Figure 1.3). The meta-
!
!
27
analysis of activation foci regarding the reverse contrast (other-traits > self-traits) yielded
2 clusters of significant ALE in, bilaterally, the PMC and in the left middle temporal
gyrus (Table 1.5, Figure 1.4).

Figure 1.3. Meta-analysis of activation foci for self-traits compared with other-traits in
relation to both kinds of other (148 foci; 22 experiments), to distant kinds of other (98
foci; 15 experiments) and to close kinds of other (50 foci; 10 experiments).
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28
Self-traits versus other-traits for close others. The meta-analysis of the activation
foci for self-traits > other-traits for only close others revealed clusters of volumes greater
than 100mm
3
bilaterally in the MPFC. In addition, one of the clusters we identified falls
outside of the standard brain, but in proximity to the left insula/ inferior frontal gyrus.
Also, the same analysis revealed additional clusters of significant ALE with smaller
volumes, namely, in the lateral prefrontal, temporal and occipital lobes (Table 1.4, Figure
1.3). The meta-analysis of activations for the reverse contrast (other-traits > self-traits)
revealed 2 clusters of volumes greater than 100mm
3
, bilaterally, in the PMC and in the
right basal forebrain, and clusters with smaller volumes, bilaterally, in the PMC, in the
right cerebellum, and in the left superior parietal lobule (Table 1.5, Figure 1.4).
Table 1.4. Meta-analysis of activation foci for self-traits compared with other-traits in
relation to both kinds of other (148 foci; 22 experiments), to distant kinds of other (98
foci; 15 experiments) and to close kinds of other (50 foci; 10 experiments).

Cluster # Brain region x y z Volume
(mm
3
)
ALE
(x10
-3
)

Self-traits > other-traits

Distant and close others
1 L medial prefrontal cortex/
anterior cingulate cortex -6 46 20 8296 20.06
2 L superior frontal gyrus/
middle frontal gyrus -22 52 30 1488 18.17
3 R middle frontal gyrus
28 52 26 736 14.52
4 L posteromedial cortex
-4 -50 46 584 18.47

Distant others

1 R medial prefrontal cortex
8 32 30 3696 16.61
2 R superior frontal gyrus
-22 52 30 1384 18.16
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!
29
3 R medial prefrontal cortex
10 58 -6 648 12.24
4 R superior frontal gyrus
-22 40 40 456 11.42
5 R superior frontal gyrus/
premotor cortex 10 12 64 416 13.00
6 L insula
-38 20 4 384 14.22
7 L angular gyrus
-56 -48 20 368 13.23
8 L posteromedial cortex
-4 -48 46 360 12.51
9 L insula
-36 12 -6 336 12.80

Close others
1
R medial prefrontal cortex
8 42 24 520 14.31
2
L medial prefrontal cortex
-8 46 20 480 13.67
3
L medial prefrontal cortex
-8 34 24 448 12.67
4
L medial prefrontal cortex
-8 50 -2 448 12.36
5
R insula/ inferior frontal gyrus
50 16 -10 328 10.42
6
R anterior cingulate cortex
medial prefrontal cortex 14 42 4 328 10.32
7
L superior frontal gyrus
-8 60 -6 96 8.92
8
R medial prefrontal cortex
2 44 10 96 8.87
9
L occipital lateral gyrus
-50 -72 -12 80 8.92
10
R middle frontal gyrus
26 52 16 80 8.60
11
R superior frontal gyrus/
frontal pole 8 64 -8 72 8.91
12
R superior frontal gyrus
14 32 52 72 8.89
13
R middle frontal gyrus
64 -38 -2 64 8.43

!
!
30
Table 1.5. Meta-analysis of activation foci for other -traits compared with self-traits in
relation to both kinds of other combined (61 foci; 12 experiments), to distant kinds of
other (23 foci; 7 experiments), and to close kinds of other (38 foci; 6 experiments).

Cluster # Brain region x y z Volume
(mm
3
)
ALE
(x10
-3
)

Other-traits > self-traits

Distant and close others

1
R posteromedial cortex
4 -58 30 1208 16.26
2
L medial temporal gyrus
-58 -16 -22 672 12.90
3
R medial temporal gyrus
48 -16 -22 296 11.19
4
R basal forebrain
-2 14 -14 288 9.88
5
R superior parietal lobule
22 -66 54 120 8.29
6
R cerebellum
18 -52 -28 80 8.89
7
R superior parietal lobule
-40 -56 52 64 8.64
8
R middle temporal gyrus
-48 30 -14 56 9.06

Distant others

1 R posteromedial prefrontal
4 -60 30 384 13.3
2 L medial temporal gyrus
-62 -8 -26 56 9.26

Close others
1 L/R posteromedial cortex
0 -52 26 456 11.73
2 L basal forebrain
-2 14 -14 352 9.88
3 R cerebellum
18 -52 -28 96 8.89
4 L superior parietal lobule
-40 -56 52 96 8.64
5 L posteromedial cortex
6 -50 18 56 8.30
6 R posteromedial cortex
-12 -58 22 56 8.17

!
!
31

Figure 1.4. Meta-analysis of activation foci for other -traits compared with self-traits in
relation to both kinds of other combined (61 foci; 12 experiments), to distant kinds of
other (23 foci; 7 experiments), and to close kinds of other (38 foci; 6 experiments).
!
!
32
Comparisons between contrasts (subtraction analyses)
Other-traits > baseline for close others versus other-traits > baseline for distant
others. A subtraction analysis did not yield differences of ALE results for other-traits >
baseline between close others and distant others. A conjunction analysis revealed an
overlap of ALE scores for other-traits > baseline between the two kinds of other in a large
cluster in the PMC (cluster 1 -MNI coordinates: -3, -54, -29; ALE: 10.2; volume: 384
mm
3
) as well as in smaller clusters in the left superior frontal gyrus (cluster 2 - MNI
coordinates: -13, 45, 51; ALE: 7,54; volume: 40mm
3
; cluster 3 - MNI coordinates: -11,
35, 50; ALE: 7, 51; volume: 32mm
3
) and in bilaterally in the PMC (cluster 4: MNI
coordinates: -8, -57, -30; ALE: 7,74; volume: 16mm
3
; cluster 5: MNI coordinates: 0, -56,
18; ALE: 7,43; volume: 8mm
3
).
Self-traits > other-traits for close others versus self-traits > other-traits for
distant others. In a subtraction analysis, ALE results for self-traits > other-traits
regarding close others were not different from those regarding distant others. Nonetheless,
a conjunction analysis revealed an overlap of ALE results for self-traits > other-traits
between the two kinds of others in three clusters in the MPFC/ACC (cluster 1 - MNI
coordinates: -5, 45, 20; ALE: 9.8; volume: 112 mm
3
; cluster 2 – MNI coordinates: 0, 44,
9; ALE: 8.7; volume: 40 mm
3
; cluster 3 - MNI coordinates: -5, 37, 24; ALE: 8.2;
volume: 24 mm
3
) and one cluster in the frontal pole (cluster 4 - MNI coordinates: 8, 62, -
6; ALE: 7.65; volume: 8 mm
3
).
Other-traits regarding close others > self-traits versus Other-traits regarding
distant others > self-traits. A subtraction analysis did not yield differences of ALE
results for other-traits > self-traits between close others and distant others. In addition,
!
!
33
conjunction analysis showed an overlap of ALE results (for other-traits > self-traits)
between the two kinds of other in a cluster in the PMC (MNI coordinates: 2, -56, 29;
ALE; 7.1; volume = 16mm
3
).
Discussion
The processes of memory retrieval and decision that support the evaluation of
one’s personality traits vary depending on the recalled material. It has been shown that
both behavioral measures and brain activity during the evaluation of one’s traits depend
on how relevant the trait is to the individual’s identity (e.g., Markus, 1977; Kuiper, 1981;
Lieberman et al., 2004). The same factors are also likely to play a role in the evaluation
of traits pertaining to another person and possibly account, at least in part, for the varied
results reviewed in the published studies. Still, a meta-analysis of those published data
may help us gain a better perspective on the problem.
The results of the present meta-analyses reveal similarities and differences
between self-traits and other-traits in terms of activation foci. Contrasted with baseline,
self-traits and other-traits engage some of the same brain structures, including CMSs such
as the MPFC and the PMC. Nonetheless, the results also reveal parametric differences
between self and other in terms of activation in CMSs as well as in the insula and basal
forebrain. The ALE results, referring to the contrast of other-traits with baseline and to
the contrasts between other-traits and self-traits, seem to indicate that these differences
may depend on the kind of other on which the study focused. We note, however, that the
subtraction analyses did not confirm an effect of the type of other in any of the contrasts.
!
!
34
The MPFC and PMC are important hubs of brain connectivity and are presumably
capable of high levels of integration (Hagmann et al., 2008; Parvizi et al., 2006). They are
known to exhibit greater activation during rest and during passive tasks than during a
variety of demanding exteroceptive tasks (reviewed in Buckner et al., 2008). This suggest
that these regions are preferentially involved in processing recalled, internally generated
representations, something that is supported by their significant involvement during mind
wandering (Mason et al., 2007), lapses of attention in externally oriented tasks
(Weissman et al., 2006) and imagining future events (Schacter et al., 2012). We believe
that their engagement in the evaluation of personality traits relates to retrieval and
assembly of memories and to involvement in decision processes. Moreover, although the
MPFC and PMC are interconnected and frequently activated during some of the same
tasks, it is probable that these structures differ from each other in terms of the scope of
representations they process.
The data derived from our meta-analyses show that the MPFC is generally more
active for self-traits than for other-traits, and, although not confirmed by the subtraction
analysis, this difference seems to be greater in the case of a distant other than a close
other. There is strong evidence that MPFC is involved in the participation of somatic
signals in processes of decision-making (Bechara et al., 2000a; 2000b). It is thus possible
that the differences of MPFC activity relate to emotion-related somatic representations in
response to the memories retrieved and the decision. These responses are probably
greater for self-traits than for other-traits but the difference is possibly smaller when
referring to a close other than when referring to a distant other. We note that the
differences between self-traits and other-traits in terms of insula activity are
!
!
35
commensurate with those found for MPFC activity. In addition, it is also possible that the
MPFC may be particularly involved in memory retrieval, namely by processing
perceptual and somatic representations of the memories retrieved and thus contributing to
a so-called “felt-rightness” during the retrieval (Moscovitch & Winocur, 2002). As
discussed earlier, individuals are likely to have greater amount of memories for self than
for another person; moreover, the memories are also likely to contain a greater amount of
information, including both perceptual and somatic, when they pertain to self than when
they pertain to another person. These differences are probably greater for a distant other
than for a close other.
Intriguingly, our meta-analyses show that the PMC is more active for other-traits
than for self-traits. The analyses relative to the contrast other-traits > self-traits derive
from a smaller number of experiments than those regarding the opposite contrast, and this
may limit the related statistical power. Nonetheless, we believe that the differences of
PMC activity relate to effort in memory retrieval. The representations that regard self are
probably more efficiently retrieved than those regarding another person, as supported by
data regarding the reaction times. Greater effort would translate into greater PMC activity.
It is possible that by abstracting from episodes and facts during their lives, individuals
have preassembled summary representations for some of their own personality traits
(Klein & Loftus, 1993). It is also possible that individuals hold similar summary
representations for aspects of their acquaintances’ personalities although that is more
likely to occur in the case of close acquaintances than distant ones (Fuhrman & Funder,
1995).
!
!
36
There is indeed evidence for involvement of the PMC in memory retrieval both
for information that regards self and for information that regards other people or things
(e.g., Binder et al., 2009; Rissman and Wagner, 2012; Wagner et al., 2005). In addition, it
has been shown that activity in the PMC relates to the retrieval effort. For example, the
PMC shows greater activity during the recall of information than during the repetition of
information (Buckner et al., 1996; Schacter et al., 1996).
It is likely that sub-areas within the same CMS are differently activated in
different conditions. For example, although the PMC is generally more active for other-
traits, it shows also a cluster of greater activity for self-traits than for other-traits in the
present meta-analysis. It has also been proposed that the MPFC is differentially activated
by self and other, with the most ventral areas more active for self and more dorsal areas
more active for other (reviewed in Amodio and Frith, 2006).
In conclusion, our results provide evidence that self-traits and other-traits may
depend on the same brain structures, including CMSs. Moreover, the differences between
self-traits and other-traits vary according to who the other is in relation to self. We
believe that these findings are linked to processes of memory retrieval and decision that
underlie the evaluation of personality traits.

!
!
37
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Chapter 2
Involvement of cortical midline structures in autobiographical self states

46
Abstract
The term autobiographical self has been used to refer to a mental state that permits
reflection on self-identity and personality and the answer to related questions (Damasio, 1999). It
requires the retrieval and integrated assembly of memories of facts and events that define an
individual’s biography. The neural mechanisms behind this state have not been fully elucidated,
but it has been suggested that cortical midline structures (CMSs) are critically involved in
processing self-related information. To date, the investigation of the involvement of CMSs in
autobiographical self processes has largely focused on the comparison between self and other in
relation to one domain of information, personality traits, and has yielded conflicting results.
Here, I investigated how activity in CMSs varies with (1) the subject of the information
(self versus an acquaintance), (2) the domain of information (personality traits versus facts), and
(3) differences across individuals regarding how descriptive and how important/relevant the
information targeted by the questions was, and regarding the amount of memory retrieved in
order to answer the questions; (4) personality differences across participants in relation to how
self-related information tends to be processed; (5) personality differences across participants in
relation to how information pertaining to other tends to be processed; (6) differences across
participants regarding the acquaintanceship. I used an fMRI block-design in which 19 participants
answered questions about traits and biographical facts, in relation to themselves and a distant
acquaintance. In addition, after the scan, the participants rated the descriptiveness and importance
of the information targeted by the questions, estimated the amount of memory retrieved to answer
the questions, and filled relevant personality questionnaires.
Our results showed that CMSs were active for both facts and traits and for both self and
other, and that the level of activity in the posteromedial cortices was generally higher for other

47
than for self. For both self and other, activity in CMSs varied also with the amount of memory
retrieved to answer the questions and with descriptiveness and importance of the information. In
addition, activity for self varied with personality differences regarding how self-information tends
to be processed. Likewise, activity for other varied with personality on personality differences
regarding how information pertaining to other tends to be processed.
These findings suggest that involvement of CMSs during the evaluation of information is
not specific for self, and depends on varied factors related to memory retrieval prompted by the
questions and to processes required to answer them.

48
Introduction

The term autobiographical self has been used to refer to a mental state that enables an
individual to reflect on self-identity and personality, and to answer related questions (Damasio,
1999). This state requires retrieval and integrated assembly of memories of facts and events
defining an individual’s biography. The neural mechanisms behind autobiographical self
processes have not been fully elucidated, but it has been suggested that cortical midline structures
(CMSs), particularly the medial prefrontal (MPFC), and posteromedial cortices (PMC), are
critically involved in processing self-related information (Northoff et al., 2004).
To date, the investigation of the involvement of CMSs in autobiographical self processes
has often focused on the comparison between “self” and “other” in relation to one domain of
information, personality traits, and has yielded conflicting results as has been noted by others
(Legrand & Ruby, 2009). For example, self-traits, contrasted with other-traits, revealed greater
activity in the MPFC and PMC (e.g., D’Argembeau et al., 2007); but elsewhere, other-traits
contrasted with self-traits yielded greater activity in these same regions (e.g., Pfeifer et al., 2007).
Interestingly, both the MPFC and PMC have been shown to consist of highly connected
hubs (Tomasi & Volkow, 2011) and to be part of the so-called default network, yielding greater
activity for internally oriented tasks than for externally oriented tasks (Buckner, Andrews-Hanna,
& Schacter, 2008). These regions do not appear to support processes specific to self but are,
rather, able to assist varied processes involving internally generated representations. Moreover, I
theorize that the involvement of CMSs during evaluative tasks used to investigate the
autobiographical self relates to the processes that underlie those tasks, namely, memory retrieval
prompted by the questions and the decisions needed to answer the questions, similarly to what
has been proposed by other authors (Legrand & Ruby, 2009).

49
Accordingly, I hypothesize that the level of activity in CMSs during such tasks is likely to
be commensurate with the level of processing related to memory retrieval (which depends, for
example, on the effort in retrieving the memories and on the complexity of the retrieved
memories), and to decision making (which depends, for example, on the effort involved in the
decision). Thus rather than being necessarily greater for self than for other, activity in CMSs may
vary with:
(1) the subject of the evaluation (e.g., whether it pertains to self, to a close other, or to a
distant other);
(2) the domain of information being evaluated (e.g., personality traits or demographic
facts);
(3) differences across participants regarding the information they have to evaluate (e.g.,
differences in relation to how well the information describes self and other, and to the
importance the information has to the participants’ image of self or of other);
(4) personality differences across participants in relation how self-related pertaining tends
to be processed (e.g., Self-Consciousness Scale [Scheier & Carver, 2005]);
(5) personality differences across participants in relation how information pertaining to
other tends to be processed (e.g., differences related to perspective taking);
(6) differences across participants regarding the acquaintanceship (e.g., the degree of
closeness of the relationship between self and other) as well as regarding how similar
self is to other in relation to the information evaluated.
Some of the above factors have already been shown to contribute to differences in
behavioral tasks (e.g., reaction times to the questions) between self and other (Symons &

50
Johnson, 1997), but have only partly investigated in imaging studies. Specifically, it has been
established that brain activity during the evaluation of traits depends on the target
of that evaluation. For example, the difference of activity in the MPFC between self and other
has been shown to depend on who the other is in relation to self (i.e., whether it is a close or a
distant other) (Denny, Kober, Wager, & Ochsner, 2012). The contribution of the other factors,
however, needs further investigation.
In this study, I tested the above set of hypotheses and investigated how brain activity
varies according to the factors listed above. To do so I conducted an fMRI block-design study, in
which participants answered questions about biographical information. The questions varied in
terms of the subject of evaluation and the domain of information being evaluated. In addition, I
measured differences across participants in relation to the factors listed above.
I used an active baseline (the one-back task) to obtain a strong contrast between the
experimental conditions and the baseline. I expected this baseline task to suspend the
introspective processes likely to occur during rest or poorly engaging tasks, and to deactivate
CMSs, given that CMSs are known to be especially active during rest (as reviewed in Buckner et
al., 2008).
The subject of the evaluation in this study was the participant (self) or a distant
acquaintance of the participant (other) (Figure 2.1). This choice of other was made in the hope of
attaining a clear distinction between self and other, and is, as explained above, likely to be a
decisive factor in the differences of brain activity between self and other. Memories for a distant
acquaintance are probably less numerous, less frequently retrieved, and less readily accessible
than autobiographical memories. In addition, it is likely that individuals are more likely to
abstract summary representations for information pertaining to themselves or close acquaintances

51
than for information pertaining to distant acquaintances (Fuhrman & Funder, 1995). Accordingly,
I expected that in this study, compared with evaluating other, evaluating self should require a
lower level of processing memory retrieval and decision-making and thus should yield a lower
level of related activity in CMSs.
The study included two domains of information: personality traits and basic facts that
define one’s identity (e.g., age, height, nationality and occupation), to which I refer as
“biographical facts” (Figure 2.1). Although both domains are part of the general knowledge a
person is likely to hold regarding one self (Klein & Gangi, 2010), biographical facts are
significantly different from personality traits (Keenan, Golding, & Brown, 1992). Specifically,
biographical facts are objective, indisputable and easily verifiable (e.g., the personal information
contained in one’s drivers license or identity card). On the other hand, personality traits are
classified in terms of valence and desirability (Anderson, 1968) and are generally associated with
an emotional significance (Klein & Loftus, 1993). Moreover, the judgment of our personality
traits depends on our life experience. The number of daily experiences that provide knowledge
regarding certain personality traits may be, however, very limited and thus one’s representations
for those traits may remain relatively ambiguous (Kuiper, 1981). In brief, compared with facts,
traits are less objective and less easily verifiable, hold a greater emotional significance. Thus the
processes of memory retrieval and decision-making pertaining to the evaluation of traits are likely
to evoke greater emotional responses and related brain activity than those processes pertaining to
the evaluation of facts.

52

Self

Other

Personality
traits

Does the work
“honest” describe
you?

Does the work
“honest” describe him
[or her]?

Biographica
l facts

Are
you a
student?

Is he [or she]
a
student?

Figure 2.1. Experimental conditions used in the fMRI study. The conditions varied according to
the subject of the evaluation (self versus other) and with the domain of information evaluated
(personality traits versus biographical facts).

Three measures were used to assess differences between the participants regarding how
biographical information was processed: (i) descriptiveness (i.e., the ratings of how well the
content of the questions described self or other); (ii) importance (i.e., how important the content
of the questions was to address the participants’ self-image or the participants’ image of their
acquaintances); and (iii) amount of memory retrieved to answer the questions (i.e., participants’
estimated number of episodes retrieved to answer the questions) (Table 2.1).

53

Table 2.1. Participants’ ratings and estimates collected after scanning. The participants rated the
information targeted by each questions in terms of descriptiveness and importance, and estimated
the amount of memories they needed to retrieve to answer the questions.

Self

Other

Descriptiveness

How well does the information
targeted by each question describe
“self”?
How well does the information
targeted by each question
describe “other”?

Importance How important to the participants’ self-
image was the information targeted by
each question?
How important to the
participants’ image of their
acquaintance was the
information targeted by each
question?

Memory
retrieved
How many memories (episodes) did the participants need to retrieve in
order to answer the questions in each condition?

Descriptiveness has been shown to relate to participants’ reaction times to the questions
about self (e.g., Markus, 1977). Specifically, it has been shown that reaction times to self-traits
questions are shorter for traits considered highly descriptive or highly non-descriptive (i.e.,
unambivalent) traits, than for traits that are considered intermediately descriptive (ambivalent)
traits. Furthermore, this difference of processing time may occur because individuals are more
likely to hold unambivalent cognitive generalizations (self-schemata, Markus, 1977) or summary
representations (Klein & Loftus, 1993) for highly descriptive or highly non-descriptive traits than

54
for intermediately descriptive traits. For these reasons, I believe that the level of CMSs activity
should be lower for individuals that considered the information highly descriptive or highly non-
descriptive because these individuals are likely to require lower level of processing related to
memory retrieval and decision making to answer the questions. To test this, I assessed the
participants’ ratings for descriptiveness and used those ratings to compute a measure of how
ambivalent the information was considered. Specifically, descriptive ambivalence scores ranged
from 0 (information that the participants rated as highly descriptive or highly non-descriptive) to
2 (information that the participants rated as equally descriptive and non-descriptive).
In addition, the importance of biographical information has also been shown to be
relevant to understand behavioral measures of processing information (Markus, 1977). I used this
measure to complement the information provided by the descriptiveness. An individual’s
importance rating for a biographical datum (independently of its descriptiveness) probably
reflects the likelihood of having given prior consideration to that information, and thus the
likelihood of having a summary representation for it. Consequently, the level of CMSs activity
should also be lower for individuals who considered the information more important because
these individuals probably required lower level of processing related to memory retrieval and
decision making to answer the questions.
The participants’ estimates of amount of memory retrieved to answer the questions were
used to assess how much retrieval of specific events or episodes each condition required.
Behavioral studies have shown that judging personality traits for both self and other may rely on
relatively more effortful process of retrieving of specific episodes (exemplars) or on a relatively
less effortful process of retrieving summary representations (Klein & Loftus, 1993). Accordingly,
I expected that level of CMSs activity should be higher for individuals who estimated greater

55
amount of memory retrieved because these individuals probably required higher level of
processing related to memory retrieval and decision-making.
Two personality measures in relation to how self-related information tends to be
processed were used: the SelfConsciousness Scale (SCS) (Scheier & Carver, 2005), and Body
Awareness Questionnaire (BAQ) (Shields, Mallory, & Simon, 1989).
The SCS assesses a person’s tendency to reflect on oneself (e.g., “ I’m always trying to
figure myself out.”) (Scheier & Carver, 2005). It thus seems likely that individuals with higher
SCS scores reflect more on self-questions than those with lower SCS scores. Consequently, I
predicted that the level of CMSs activity should be positively correlated with individuals’ SCS
scores.
The BAQ assesses a person’s tendency to notice body sensations (e.g., “I notice specific
bodily reactions to being over-hungry.”) and to predict body-related processes in healthy
conditions (e.g., “ I can tell in advance when I go to bed how well I will sleep that night.”) as well
as the onset of certain diseases (“ I know in advance when I’m getting the flu.”) (Shields,
Mallory, & Simon, 1989). It seems likely that level of emotion-related somatic processing elicited
by the questions should be higher for individuals with higher BAQ scores than for those with
lower BAQ scores. Accordingly, I predicted that participants’ BAQ scores should correlate their
brain activity in emotion-related somatic regions (e.g., insular cortices); in addition, given that
traits hold a greater emotional value than facts, such correlation should be greater for traits than
for facts.
Personality measures in relation to how information pertaining to others tends to be
processed were assessed using two scales part of the Interpersonal Reactivity Index (IRI; David,
1980): the Perspective Taking (PT), and Empathic Concern (EC) scales.

56
The PT assesses a person’s tendency to adopt someone else’s perspective (e.g., “I try to
look at everybody’s side of disagreement before I make a decision”); the EC measures a person’s
tendency to experience “warmth, compassion and concern” for someone going through some
negative experiences (“ I am quite touched by things that I see happen”) (David, 1980). It seems
likely that participants with higher scores for PT, EC, or both, are associated with a greater level
of emotion-related processing in response to other-related questions than participants with lower
scores for those scales. Consequently, I predicted that participants’ PT and EC scores should both
positively correlate with activity generated in emotion-related somatic regions (e.g., insular
cortices) during the “other” conditions. Once again, given that traits hold a greater emotional
value, this correlation should be stronger for other-traits than for other-facts.
The relationship between the participants and their acquaintances (acquaintanceship) was
assessed using two measures: (i) the acquaintanceship length (i.e., for how long the participant
knew the acquaintance); and (ii) the descriptiveness similarity scores, which were computed by
comparing, for each question, the participants’ descriptiveness ratings for self with those for
other. It is likely that one’s knowledge of an acquaintance is commensurate with both the
acquaintanceship length and similarity scores. Accordingly, the level of processing related to
memory retrieval and decision making necessary to answer questions about other, and
consequently the level of activity in CMSs, should correlate negatively with acquaintanceship
length and similarity. Moreover, it is possible that the level of emotion-related processing elicited
by the questions about other is commensurate with acquaintanceship length and similarity.
Accordingly, activity in regions involved in emotion-related processing during other-conditions
should be positively correlated with acquaintanceship length and similarity scores.

57
Figure 2.2. Summary of the co-variables investigated in the study. This study explored how
brain activity generated for each condition (Figure 2.1) varied according differences across
individuals in relation to (i) the information targeted in the questions, (ii) personality measures
regarding how self-related information tends to be processed, (iii) personality measures regarding
how information pertaining to others tends to be processed, and (iv) the acquaintanceship
between self and other (acquaintanceship length, and similarity scores).

Regarding
the
conditions

How self –related
information tends
to be processed

How information
pertaining to other
tends to be processed

Relationship
between
self and other

Importance

Ambiguity

Self Consciousness
Scale

Perspective Taking
Scale

Acquaintanceship
length

Memory

Body Awareness
Questionnaire

Empathetic Concern
Scale

Similarity

58
Methods
Participants
Twenty native English speakers, right-handed, with no history of neurological diseases,
were recruited from the University of Southern California community. The participants were paid
for their participation, and provided written informed consent following the Institutional and
Federal Guidelines. Data from one participant had to be excluded due to motion artifacts. The
final sample comprised 19 participants (10 female, and 9 male; 20.1 +/- 1.3 years old).
Materials and Procedures
Before the scanning, participants were asked to select an acquaintance of the same gender,
whom they knew well enough to answer questions about his/her personality and life in general,
but with whom they did not have a strong emotional connection (similar criteria to those used by
Modinos, et al., 2009). Mean age of the acquaintances was 20 (SD = 1.2) years old, and mean
length of acquaintanceship was 25.8 (SD = 27.95) months.
The stimuli were questions organized in four conditions (Figure 2.1): (i) self-traits, in
which the participants were asked to judge if specific personality traits described them accurately
(e.g., “Does the word honest describe you?”); (ii) self-facts, in which participants were asked to
verify if specific autobiographical facts were correct (e.g., “Are you a student?”); (iii) other-traits,
in which the participants were asked to judge if specific personality traits described their
acquaintances properly (e.g., “Does the word honest describe him [or her]?”); ; (iv) other-facts,
in which the participants were asked to verify if specific biographical facts about their
acquaintances were correct (e.g., “Is he [or she] a student?”). The content of the questions was
the same for self and for other. The trait-questions comprised 27 negative traits and 27 positive
traits, derived from a published list of personality traits (Anderson, 1968). The fact-questions
covered general aspects of one’s life, such as age, height, weight, ethnicity, nationality,

59
occupation, typical means of transportation, household and physical appearance. The participants
had three options to answer the questions: “yes”; “no”; or other (when the participants did not
know the correct answer, or did not consider “yes” or “no” as the correct answer).
I used MATLAB (The Mathworks) and Psychophysics Toolbox Version 3 (Brainard,
1997) to present the stimuli (projected on a screen, which the participants saw through a mirror
mounted on the head coil) and to record the participants’ responses (given with button presses
using the right h).
The fMRI experiment followed a block design. Each run contained three blocks for each
condition. The order of the blocks was randomized in each run and for each participant. Each
block lasted 24 seconds and contained a random selection of six questions. Each question was
presented for four seconds, during which participants were asked to provide the requested answer.
Blocks of stimuli were separated by a 24-second block of the one-back-task baseline, in which
the participants saw a series of letters and had to decide whether each of the letters was identical
the one immediately preceding it.
Image Acquisition
Magnetic resonance images were acquired with a 3-Tesla Siemens MAGNETON Trio
System. I used the following parameters for echo-planar image (EPI) acquisition: TR = 2000ms,
TE = 25ms, flip angle = 90˚, 64 x 64 matrix, in-plane resolution 3.0 mm x 3.0 mm, 41 transverse
slices, each 3 mm thick, and field of view covering the whole brain. Each functional run lasted
9.7 minutes and consisted of 291 volumes. All participants completed three runs, but due to a
problem with the software, one participant did not complete two blocks (one for other-traits, and
one for other-facts); the EPI volumes corresponding to these blocks were not included in the
analysis. For purposes of registration, I also acquired structural images (T1-weighted

60
magnetization-prepared rapid gradient echo, MPRAGE) using the following parameters: TR =
1950 ms, TE = 2.3 ms, flip angle = 7˚, 256 x 256 matrix, 193 coronal slices, 1 mm isotropic
resolution.
Questionnaires and Analysis
After the scanning, the participants estimated the amount of memories (e.g., particular
episodes) they recalled in order to answer the questions in each condition, using a 7-point Likert
scale (1: I did not recall any particular memory.; 7: I recalled many episodes…). The
participants also rated the content of each self-question in terms of how well it described them
(self-descriptiveness) and of how important (self-importance) it was to their identities; likewise,
for the content of each other-question relative to how well it described their acquaintances
(other-descriptiveness) and how important it was to their representations of the acquaintances
(other-importance). For these ratings, each question was transformed into a statement, (“You are
a student.”), and Likert scales were used. The scales ranged as follows: (i) for self-
descriptiveness, from 1 (… definitely untrue or uncharacteristic of me.) to 5 (…very true or
strongly characteristic of me.); (ii) for self-importance, from 1 (… definitely not important to my
identity.) to 5 (… absolutely important to my identity.); (iii) for other-descriptiveness, from 1 (…
definitely untrue or uncharacteristic of him /her.) to 5 (… very true or strongly characteristic of
him /her.); (iv) for other –importance, from 1 (… definitely not important to the image I have of
him/her.) to 5 (… absolutely important to the image I have of him/her).
The ratings of descriptiveness were recoded in order to assess how ambivalent
(descriptive ambivalence) the participants considered the questions, as follows: ratings 5 and 1
were recoded into 0, ratings 4 and 2 were recoded into 1, and rating 3 was recoded into 2.

61
In addition, the ratings of descriptiveness were used to compute a measure of how similar
the participant was to the acquaintance, using the following equation for each question:
descriptiveness similarity = 4 – (descriptiveness rating for self - descriptiveness rating for other).
All participants answered the following questionnaires: (1) Self-Consciousness Scale
(Scheier & Carver, 2005); (2) Body Awareness Questionnaire (Shields, Mallory, & Simon,
1989).Interpersonal Reactivity Index, which includes the Perspective Taking Scale, and the
Empathic Concern Scale (David, 1980 and 1983).
All behavioral data, including repeated measures ANOVA and Pearson correlations, were
analyzed using PASW Statistics 18.0.

Image Processing and Analysis
The functional data were preprocessed and analyzed with FSL (FMRIB's Software
Library, www.fmrib.ox.ac.uk/fsl). Before the statistical analysis was performed, the following
steps were applied: (i) motion correction using MCFLIRT (Jenkinson et al., 2002); (ii) slice-
timing correction using Fourier-space time-series phase-shifting; (iii) non-brain removal using
BET (Smith, 2002); (iv) spatial smoothing using a Gaussian kernel of FWHM 5mm; (v) grand-
mean intensity normalization of the entire 4D dataset by a single multiplicative factor; (vi) high-
pass temporal filtering (Gaussian-weighted least-squares straight line fitting, with sigma = 50.0
s). The participants’ data were registered to their high-resolution structural images (with 7
degrees of freedom) and to a standard space (MNI-152 atlas, with 12 degrees of freedom) using
the FMRIB's Linear Image Registration Tool (Jenkinson et al., 2002) and FNIRT nonlinear
registration (Andersson et al., 2007). The data were first analyzed using FSL's implementation of
the general linear model, FEAT Version 5.98. The model included motion parameters, and four

62
separate regressors, one for each experimental condition. Each regressor was derived from the
convolution of the corresponding task design and a gamma function representing the
hemodynamic response. Time-series statistical analysis was carried out using FILM with local
autocorrelation correction (Woolrich et al., 2001). The functional data of the three runs for each
participant were combined using a fixed-effect model, which forces the random effects variance
to zero in FLAME (FMRIB's Local Analysis of Mixed Effects; Woolrich et al., 2004). The data
from all the participants were then analyzed in a higher-level mixed-effects analysis using
FLAME.
Additional higher-level mixed-effects analyses were performed using behavioral measures
(Figure 2.2) as co-variables (between-subject factors), namely:
(1) For each of condition, (i) participants’ mean ratings for descriptiveness and
importance, and (ii) participants’ estimates of the amount of memories they recalled;
(2) For each self-condition, (i) participants’ mean SCS scores and (ii) participants’ mean
BAQ scores;
(3) For each other-condition, (i) participants’ Perspective-Taking (PT) scores, (ii)
participants’ Empathic-Concern (EC) scores, and (iii) mean length of
acquaintanceship;
(4) For self-other contrasts (self-facts > other-facts; self-traits > other-traits; [self-facts +
self-facts] > [other-facts + other-traits]), (i) participants’ PT scores, (ii) participants’
EC score, (iii) mean length of acquaintanceship, and (iv) mean participants’
descriptiveness similarity scores.
(5) For facts-traits contrasts (for self, for other or for both), participants’ BAQ scores.

63
The following threshold was applied to all statistical images: clusters determined by Z >
2.3 and corrected cluster size significance threshold of p = .05 (Worsley, 2001).
In addition, a conjunction analysis of the higher-level results for each condition compared
with the baseline, using easythresh_conj script in FSL (Nichols, 2007). For this analysis, a whole-
brain as a mask and a threshold of Z > 2.3, p = .05 were used.

Results
Behavioral Data
Reaction Time. Questions about self were answered faster than those about other, F(1,18)
= 31.42, p < .001. In addition, questions about facts were answered faster than those about
personality traits, but this difference did not reach the level of statistical significance, F(1,18) =
4.03, p = .60. A statistically significant interaction between the subject of the evaluation (self or
other) and the domain of information targeted by the questions (facts or traits) was observed,
F(1,18) = 10.17, p < .005. Pairwise comparisons (p values adjusted for multiple comparisons
using Bonferroni) revealed that differences of reaction times between self and other were
statistically significant for facts (p < .0001) but did not reach statistical level of significance for
traits (p < .24); and that differences of reaction times between facts and traits were statistically
significant for self (p < .016) but not for other ( p < 2.704) (Table 2.2).

Reaction time according to the valence of the traits. No statistically differences of
reaction times were observed for negative traits and positive traits, for self or for other (Table
2.3).

64
Reaction time according to descriptiveness ratings. Facts rated 1 or 5 (extremes) in terms
of descriptiveness showed shorter reaction times than facts rated intermediate values of
descriptiveness (Figure 2.3). These differences reached statistical significance for the comparison
between self-facts rated 1 for descriptiveness and self-facts rated 2 for descriptiveness, F (1,17) =
12.075, p < .003; and self-facts rated 5 for descriptiveness and self-facts rated 2, F (1,17) =
5.381, p < .033. In addition, reaction times for other-facts rated 5 for descriptiveness were also
shorter than those for other-facts rated 3 for descriptiveness F(1,17) = 5.424, p < .032.
Traits showed a similar tend (Figure 2.3). These differences reached only statistically
significance for the comparison between self-traits rated 1 for descriptiveness and self-traits rated
2 for descriptiveness, F (1,18) = 9.440, p < .007; for self-traits rated 5 and self-traits rated 2 for
descriptiveness, F (1,17) = 6.855, p < .018.
Reaction time according to importance ratings. The comparison of mean reaction times
according to the importance ratings was limited by the fact that not all participants used the full
range of the importance ratings (e.g., only 12 participants rated any self-traits as 1 for
importance). Nonetheless, the analysis revealed similar trends to those described above for
descriptiveness.
Facts rated 1 or 5 (extremes of importance) showed shorter reaction times than facts rated
intermediate ratings of importance (Figure 2.3). These differences were statistically significant
for the comparison between self-facts rated 1 for importance and self-facts rated 2 in the same
regard, F (1,17) = 6.125, p < .048; and for the comparison between other-facts rated 5 for
importance and (i) other-facts rated 2, F (1,12) = 7.131, p < .020, and (ii) other-facts rated 3, F
(1,12) = 5.622, p < .035. On the other hand, for other, facts rated 1 for importance were
associated with longer reaction times than facts rated 5 for importance, F (1,12) = 6.287 p < .028.

65
Traits rated 1 or 5 (extremes) in terms of importance were also associated with shorter
reaction times than traits rated intermediately for importance (Figure 2.3). These differences
reached only statistically significance for the comparison between self-traits rated 5 for
importance and self-traits rated 2 for importance, F (1, 9) = 6.125, p < .035, and self-traits rated
3, F (1,12) = 6.391, p < .027.

Figure 2.3 Reaction time (M and SEM) according to descriptiveness and importance ratings.

Descriptiveness. Both for facts and for traits, the information targeted by the questions
was considered less ambivalent (i.e., descriptiveness ratings were closer to highly descriptive or
highly non- descriptive) for self than for other, F(1,18) = 4.619, p < .045 (Table 2.3). In addition,

66
facts were also considered less ambivalent than traits, F(1,18) = 54.16 , p < .0001 (Table 2.3). No
statistically significant interaction between the subject of the evaluation (self or other) and the
domain of information targeted by the questions (facts or traits) was observed for descriptiveness
ambivalence scores.
In addition, descriptiveness ratings were greater for positive traits than for negative traits,
for both self and other, F(1, 18) = 168.752, p < .0001 (Table 2.3). A statistically significant
interaction between the subject of the evaluation (self or other) and the valence of the traits
(negative or positive) was observed for descriptiveness ratings, F(1, 18) = 4.855, p < .041.
Pairwise comparisons (p values adjusted for multiple comparisons using Bonferroni) showed that
descriptiveness ratings were greater for positive traits than for negative traits for self (p < .0001),
and for other (p < .0001); and that descriptiveness ratings were greater for self than for other in
relation to positive traits (p < .008) but not in relation to negative traits (p < 1.584).
Importance. Participants’ ratings of importance were greater for self than for other, F(1,
18) = 8.85, p < .008. Furthermore, for both self and other, ratings of importance were greater for
traits than for facts, F(1, 18) = 31.27, p < .001. A statistically significant interaction between the
subject of the evaluation (self or other) and the domain of information targeted by the questions
(facts or traits) was observed, F(1,18) = 4.431, p < .05. Pairwise comparisons (p values adjusted
for multiple comparisons using Bonferroni) revealed that participants importance ratings were
greater for traits than for facts, both for self (p < .0001) and for other (p < .001); in addition,
participants importance ratings were greater for self than for other in relation to facts (p < .004)
but not in relation to traits (p < .504).
Positive traits were considered more important than negative traits for both self and other,
(Table 2.3), F(1, 18) = 18.064, p < .0001, but a statistically significant interaction between the

67
subject of the evaluation (self or other) and the valence of the traits (negative or positive) was
found for importance ratings, F(1, 18) = 8.16, p < .010. Pairwise comparisons (p values adjusted
for multiple comparisons using Bonferroni) showed that participants’ importance ratings were
greater for positive traits than for negative traits, both for self (p < .0001) and for other (p <
.044); in addition, participants’ importance ratings were greater for self than for other in relation
to positive traits (p < .016) but not in relation to negative traits (p < 2.444).

Memory retrieval. Questions about other were associated with a greater amount of
reported memory retrieval than the questions about self, both for biographical facts and for traits,
F(1, 18) = 32.02; p < .001 (Table 2.2).
Table 2.2. Mean reaction times, descriptive ambivalence scores (ranging from 0 to 2), importance
ratings (ranging from 1 to 5), and memory estimates (ranging from 1 to 5) for facts and traits
relative to self and to other.

Reaction Times Descriptive
ambivalence
Importance Memory

Condition M SD M SD M SD M SD

Self
Facts 1.37 .22 0.17 .03 2.49 .67 2.8 1.6
Traits 1.51 .27 0.59 .06 3.28 .01 3.4 1.8

Other
Facts 1.57 .21 0.26 .05 2.14 .70 4.5 1.5
Traits 1.58 .30 0.68 .08 3.12 .92 4.6 1.5

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Table 2.3. Descriptiveness (1-5) and importance ratings (1-5) for negative and for positive traits
regarding self and other

Descriptiveness Importance

Traits M SD M SD

Self
Negative 1.62 .39 2.73 1.41
Positive 4.12 .37 3.83 .70
Other
Negative 1.77 .76 1.77 1.26
Positive 3.64 .61 3.43 .78

Personality measures. Mean participants’ personality scores were as follows (Table 2.4):
(i) for SCS, M = 56.05, SEM = 3.32; (ii) for BAQ, M = 75.53 SEM = 3.78; (iii) for PT, M = 18.0,
SEM = 1.29; and for EC, M = 19.42; SEM = 0.99.
Table 2.4. Participants’ mean scores for the personality measures used in this study.

Personality Measure M

SEM
Self-consciousness scale (SCS) 56.05 3.32

Body awareness questionnaire (BAQ) 75.53 3.78

Perspective taking scale (PT) 18.00 1.29

Empathic concern scale (EC)

19.42 0.99

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Acquaintanceship. The participants knew their acquaintances for M = 25.79 months
(SEM = 6.41 months). In addition, participants’ mean descriptiveness similarity scores were M =
3.91, SEM = .037 for facts, and M = 3.85, SEM = .066, for traits.

Correlation between behavioral measures. Mean reaction time for other-facts correlated
negatively with mean importance ratings for other-facts, r (18) = -.548, p < .015.
Participants estimated number of memories reported to answer questions about self-facts
correlated positively with their SCS scores, r (19) = .611 p < .005, and negatively with their
BAQ scores, r (19) = -.555, p < .014.
Participants’ descriptiveness similarity scores for traits correlated negatively with
acquaintanceship lengths, r (19) = -.682, p < .001. Also, participants’ SCS scores correlated
negatively with BAQ scores, r (19) = -.663, p < .002.

Functional Imaging Data
Task versus baseline (one-back-task). A conjunction analysis revealed that the four
conditions, compared with baseline, yielded greater signal in, bilaterally, the MPFC, PMC,
cuneus, orbitofrontal cortex, basal forebrain, inferior frontal gyrus, middle temporal gyrus,
temporal pole, hippocampus, cerebellum, and thalamus, and in the left middle and superior
frontal gyri, lateral occipital cortex, angular gyrus, amygdala, and caudate (Figure 2.4, Table 2.5).

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Figure 2.4. Conjunction analysis for the experimental conditions versus baseline. The images
correspond to clusters (Z score > 2.3; cluster size probability p < .05) in CMSs.

Self versus other. No regions of greater activity for self compared with other were
detected for traits or for traits combined with facts. However, self-facts compared with other-facts
were associated with greater activity in the right middle temporal gyrus, in the left postcentral
gyrus, and bilaterally in the superior temporal, supramarginal and angular gyri (Table 2.6). Other,
compared with self, was associated with greater activity in the PMC for traits and facts combined
(Figure 2.5, Table 2.6). Other-traits compared with self-traits were associated with greater
activity in the left lateral occipital cortex, and bilaterally in the PMC (Figure 2.5, Table 2.6).

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Table 2.5. Task versus baseline. Coordinates (x, y, z; MNI-152 standard space ) and Z-scores
correspond to the activation peaks (clusters Z > 2.3; cluster probability p < .05) from a
conjunction analysis of each condition minus baseline.

Structure

H

x

y

z

Z

Medial prefrontal cortex L -2 60 -14 5.67
R 2 52 -16 4.95
Posteromedial cortex L -6 -54 20 6.17
R 2 -52 20 5.25
Cuneus L -2 -82 10 5.44
R 2 -82 14 5.01
Inferior frontal gyrus L -48 34 -10 6.18
R 50 34 -12 4.55
Middle frontal gyrus L -44 12 54 4.20
Superior frontal gyrus L -6 20 62 5.36
Middle temporal gyrus L -50 -38 -4 5.93
R 56 8 -28 3.93
Temporal pole L -50 16 -18 4.81
R 46 22 -32 4
Lateral occipital / angular gyrus L -50 -64 28 5.19
Basal forebrain/ orbitofrontal L -30 14 -26 5.03
R 26 14 -24 2.87
Hippocampus L -20 -28 -8 5.49
R 24 -26 -8 5.11
Amygdala L -16 -6 -18 3.43
Cerebellum L -18 -90 -26 5.13
R 26 -86 -34 6.38
Caudate L -10 8 10 4.73
Thalamus L -4 -14 8 4.22
R 6 -10 0 3.22

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Figure 2.5. Other versus self. The images correspond to clusters (Z score > 2.3; cluster size
probability p < .05) in CMSs.

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Table 2.6. Self versus other. Coordinates (x, y, z; MNI-152 standard space ) and Z-scores
correspond to the activation peaks (clusters Z > 2.3; cluster probability p < .05).

Structure

H

x y z

Z

Self > other
Facts
Postcentral gyrus L -66 -18 22 2.97
Supramarginal gyrus L -64 -42 32 4.13
R 66 -38 42 3.83
Angular gyrus L -58 -54 16 2.97
R 66 -48 34 3.66
Superior temporal gyrus L -58 -54 16 2.97
R 66 -28 20 2.66
Middle temporal gyrus R 64 -46 4 3.52

Other > self
Facts
Posteromedial cortex L/R 0 -70 26 4.22
L -8 -48 0 3.62
Posteromedial cortex R 4 -54 18 3.78

Traits
Posteromedial cortex L -2 -68 22 4.59
R 6 -56 18 5.36
Lateral occipital cortex L -42 -66 52 3.46

Facts and traits combined
Posteromedial cortex L -8 -48 2 4.77
R 6 -56 18 5.8

Facts versus traits. Facts (self-facts and other-facts combined) compared with traits (self-
traits and other-traits combined) yielded greater activity in the left amygdala, caudate, basal
forebrain, pons and medulla, and bilaterally in MPFC, PMC, middle frontal gyrus, precentral
gyrus, middle and inferior temporal gyri, angular gyrus, lateral occipital, fusiform gyrus,
hippocampus, cerebellum, thalamus, and mesencephalon.

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When self and other were analyzed separately, the following differences were observed:
(i) self-facts compared with self-traits were associated with greater activity in the left
supramarginal gyrus and amygdala, and bilaterally in the MPFC, PMC, middle
frontal gyrus, precentral gyrus, middle and inferior temporal gyri, angular gyrus,
lateral occipital cortex, fusiform gyrus, hippocampus, and basal forebrain (Figure
2.6, Table 2.7);
(ii) self-traits compared with self-facts were associated with greater activity in the left
insula, inferior frontal gyrus and orbitofrontal cortex, and in the right lateral
occipital cortex (Figure 2.6, Figure 2.7, Table 2.7);
(iii) other-facts compared with other-traits were associated with greater activity in the
left amygdala, supramarginal gyrus, thalamus, pons and medulla, and bilaterally in
the MPFC, PMC, cuneus, middle frontal gyrus, precentral gyrus, middle and
inferior temporal gyri, angular gyri, lateral occipital cortex, fusiform gyrus,
hippocampus, and cerebellum (Figure 2.6, Table 2.8);
(iv) other-traits compared with other-facts did not show any statistically significant
differences.

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Figure 2.6. Facts versus traits. The images correspond to clusters (Z score > 2.3; cluster size
probability p < .05) in CMSs.

Figure 2.7. Self-traits versus self-facts. Greater signal was found in the insula and inferior frontal
gyrus.

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Table 2.7. Self-facts versus self-traits. Coordinates (x, y, z; MNI-152 standard space ) and Z-
scores correspond to the activation peaks (clusters Z > 2.3; cluster probability p < .05) for facts >
traits, and traits > facts.

Structure

H

x

y

z

Z

Facts > traits
Medial prefrontal L -10 26 -16 4.92
R 8 30 -18 5.06
Posteromedial L -4 -64 20 6.04
R 2 -58 20 5.98
Middle frontal gyrus L -24 18 44 5.7
R 28 18 48 5.83
Precentral gyrus L -42 0 30 4.13
R 50 4 8 2.99
Middle temporal gyrus L -56 -36 -12 5.24
R 64 -38 -6 4.54
Inferior temporal gyrus L -62 -52 -12 5.12
R 58 -42 -12 4.96
Angular gyrus L -50 -56 40 4.9
R 60 -54 30 5.2
Supramarginal gyrus L -56 -48 36 3.98
Lateral occipital L -40 -76 42 6.72
R 48 -70 32 6.83
Fusiform gyrus L -30 -38 -18 5.5
R 26 -38 -18 3.52
Hippocampus L 28 -24 -28 3.69
R -26 -14 -26 3.52
Amygdala L -14 -6 -16 2.51
Basal forebrain L -8 -6 -16 2.51
R 8 6 -16 3.15

Traits > facts
Inferior frontal gyrus L -54 22 -6 4.26
Insula L -40 14 -12 3.01
Orbitofrontal L -42 20 -14 3.16
Lateral occipital R 42 -92 8 4.71

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Table 2.8. Other-facts compared with other-traits. Coordinates (x, y, z; MNI-152 standard space )
and Z-scores correspond to the activation peaks (clusters Z > 2.3; cluster probability p < .05) for
other-facts > other-traits.

Structure

x

y

z

Z

Medial prefrontal L -8 32 -16 4.3
R 10 36 -18 3.88
Posteromedial L -4 -60 16 5.79
R 2 -54 12 5.01
Middle frontal gyrus L -24 14 48 5.44
R 28 18 54 4.9
Precentral gyrus L -38 -4 56 4.24
Cuneus L -6 -66 4 4.71
R 6 -76 2 4.73
Middle temporal gyrus L -60 -14 -14 4.92
R 60 -32 -10 3.6
Inferior temporal gyrus L -62 -52 -14 5.41
R 60 -46 -14 4.5
Angular gyrus L -50 -56 50 4.5
R 50 -84 44 3.23
Supramarginal gyrus L -52 -52 20 4.07
Lateral occipital L -36 -72 40 5.53
R 48 -70 34 6.16
Fusiform gyrus L -30 -38 -18 5.02
R 32 -28 -24 3.7
Hippocampus L -22 -12 -26 4.52
R -20 -12 -30 4.21
Amygdala L -18 -8 -16 4.21
Cerebellum L -12 -74 -28 4.8
R 8 74 -28 4.33
Thalamus L -16 -30 -2 2.93
Pons L -4 -32 -32 3.81
Medulla L -2 -40 -46 2.8

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Behavioral covariate analysis
Ambivalence and importance. For each condition, participants’ mean descriptiveness
ambivalence scores, and importance ratings were explored simultaneously as between-subjects
factors.
Participants’ mean descriptiveness ambivalence scores correlated positively with brain
activity for three conditions (Table 2.9):
(i) for self-facts, bilaterally in medial prefrontal cortex anterior cingulate cortex,
superior and middle frontal gyri, and cerebellum;
(ii) for self-traits, bilaterally in the paracentral gyrus, posteromedial cortex, precentral
and postcentral gyri, superior parietal lobule and pons, and in the right middle
frontal gyrus and left mesencephalon;
(iii) for other-traits, bilaterally in the medial prefrontal cortex, posteromedial cortex,
and cerebellum, in the right frontal pole and orbitofrontal cortex, and in left
postcentral gyrus/ superior parietal lobule.

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Table 2.9. Brain activity and descriptiveness ambivalence scores. Coordinates (x, y, z; MNI-152
standard space) and Z-scores correspond to the activation peaks (clusters Z > 2.3; cluster
probability p < .05) positively correlated with participants’ mean ambivalence scores.

Structure H x y z Z

Self- facts

Medial prefrontal cortex/ superior frontal gyrus

L -10 38 34 3.75
Medial prefrontal cortex/anterior cingulate cortex L -6 48 6 3.11
R 2 50 6 3.24
Middle frontal gyrus L -18 40 30 3.35
R 14 38 40 3.79
Cerebellum L -44 -52 -36 4.09

R 46 -48 -38 4.36

Self-traits
Paracentral gyrus L -4 -34 70 3.15
R 6 -36 68 2.31
Posteromedial cortex L -4 -78 46 3.47
R 6 -52 62 2.8
Middle frontal gyrus R 40 52 24 4.13
Precentral gyrus/ post central gyrus/ superior parietal lobule L -34 -30 50 4.88
R 38 -34 46 3.99
Superior parietal lobule R 48 -52 30 3.57
Mesencephalon L -2 -24 -20 3.89
Pons R/L 0 -20 -32 3.65
Paracentral gyrus L -4 -34 70 3.15

Other-traits

Frontal pole R 14 54 -10 3.81
Orbitofrontal cortex R 8 30 -24 3.57
Medial prefrontal cortex L -2 32 -20 2.66
R 2 32 -24 3.95
Posteromedial cortex L -8 -70 54 3.17
R 14 -74 56 3.86
Cerebellum L -2 -66 -10 3.77
R 2 -74 -14 3.83
Postcentral gyrus/ superior parietal lobule

L
-42 -48 58 3.56

80

Participants’ mean importance ratings correlated positively with brain activity for self
traits: bilaterally in orbitofrontal cortex, basal forebrain, medial prefrontal cortex, anterior
cingulate cortex, paracentral gyrus, posteromedial cortex, caudate, putamen, insula and superior
temporal gyrus, and in the left postcentral gryus (Table 2.10).

Table 2.10. Brain activity and importance ratings for self-traits. Coordinates (x, y, z; MNI-152
standard space ) and Z-scores correspond to the activation peaks (clusters Z > 2.3; cluster
probability p < .05) negatively correlated with participants’ mean importance ratings for self-
traits.

Structure

H

x

y

z

Z

Self - traits

Orbitofrontal cortex/basal forebrain R 18 30 -22 3.11

L -22 22 -20 4.23
Medial prefrontal cortex/anterior cingulate cortex R 4 38 -14 3.61

L -2 34 -10 3.54
Paracentral gyrus R 6 -40 68 3.61

L -2 -36 70 4.62
Posteromedial cortex R -4 -50 64 3.65

L 6 -52 62 3.29
Caudate/ putamen R 6 12 -8 4.1
L -16 16 -12 4.79
Postcentral gyrus/ superior parietal lobule L -64 -28 14 3.85
Superior temporal gyrus L -58 -6 2 3.25
Insula/ superior temporal gyrus R 48 -22 10 3.85
Insula L -36 -18 2 3.0

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Amount of memory retrieved. Participants’ estimates of the amount of memory retrieved
correlated positively with signal in three conditions (Table 2.11):
(i) for self-facts, in the left precuneus, postcentral gyrus and lateral occipital lobe, and
in the right inferior frontal, superior temporal, middle temporal, and supramarginal
gyri;
(ii) for self-traits, in the right putamen, thalamus, internal and external capsule, and
bilaterally in the medial prefrontal region, anterior cingulate cortex, middle frontal
gyrus, orbitofrontal region and frontal pole;
(iii) for other-facts, in the left paracentral gyrus, precuneus, postcentral gyrus and
superior parietal lobule.

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Table 2.11. Brain activity and memory retrieval estimates ratings for self and other. Coordinates
(x, y, z; MNI-152 standard space) and Z-scores correspond to the activation peaks (clusters Z >
2.3; cluster probability p < .05) positively correlated with participants’ memory estimates.

Structure H x y z Z

Self

Facts

Posteromedial cortex L -6 -48 54 3.35
L -20 -44 66 3.93
Lateral occipital cortex L -12 -68 54 3.69

L -16 -68 52 3.66
Inferior frontal gyrus R 66 -14 12 4.16
Superior temporal gyrus R 66 -30 16 3.8
Superior temporal gyrus/middle temporal gyrus R 52 -22 6 3.2
Supramarginal gyrus R 46 -40 26 3.32

Traits
Medial prefrontal cortex L -10 64 10 4.46
R 10 64 10 3.28
Anterior cingulate cortex / medial prefrontal cortex L -4 36 24 2.79
R 4 30 34 3.71
Middle frontal gyrus L -20 40 40 4.71
R 42 38 26 3.83
Frontal pole/ orbitofrontal cortex L -18 52 -14 2.46
R 28 46 -14 4.54
Orbitofrontal cortex R 28 54 -18 3.7
Putamen R 24 2 0 3.25
Thalamus R 18 -20 8 2.56
Internal capsule R 16 0 14 3.96
External capsule R 26 16 -8 3.21

Other
Facts

Paracentral gyrus L -4 -24 76 4.03
Posteromedial cortex L -4 -46 60 3.31
Postcentral gyrus L -14 -44 68 3.55
Superior parietal lobule L -18 -50 68 3.8

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Self-consciousness scale. Participants’ SCS scores correlated positively with brain activity
for self as follows:
(i) for self-facts, bilaterally in the anterior cingulate cortex, posteromedial cortex,
basal forebrain, basal ganglia, thalamus and cerebellum, and right middle frontal
and supramarginal gyri, and left insula;
(ii) for self-traits, bilaterally in the caudate, thalamus, and cerebellum, and in the left
middle frontal gyrus and putamen/ pallidum.

Body-awareness questionnaire. Participants’ BAQ scores correlated negatively with signal for
self as follows (Table 2.13):
(i) for self-facts, bilaterally the anterior cingulate cortex, medial prefrontal cortex,
posteromedial cortex, insula, basal ganglia, and cerebellum; and in the left middle
and inferior frontal gyri, and fusiform gryus;
(ii) for self-traits, bilaterally in the putamen/ pallidum, thalamu, mesencephalon, and
cerebellum; and in the left posteromedial cortex, superior parietal lobule, angular
gyrus and insula.

In addition, participants’ BAQ scores correlated positively with signal yielded for traits >
facts as follows: (i) for self, in the right angular gyrus and insula; (ii) for other, in the
posteromedial cortex (Table 2.14).

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Table 2.12. Brain activity for self and participants’ Self-Consciousness scale (SCS) scores.
Coordinates (x, y, z; MNI-152 standard space) and Z-scores correspond to the activation peaks
(clusters Z > 2.3; cluster probability p < .05) positively correlated with participants’ SCS scores.

Structure

x y z

Z

Facts
Anterior cingulate cortex L -6 2 36 3.32
Anterior cingulate cortex/ medial frontal gyrus R 12 2 36 3.39
Posteromedial cortex L -6 -54 64 4.03
R 4 -46 48 3.6
Basal forebrain L -20 8 -16 2.78
R 18 8 -16 2.41
Middle frontal gyrus R 42 22 24 3.71
Supramarginal gyrus R 62 -38 18 3.91
Insula L -36 -16 8 2.7
Parahippocampal formation L -18 -28 -12 3.04
Caudate L -18 0 18 3.48
R 12 -8 18 3.79
Pallidum/ putamen L -16 0 -10 3.34
R 22 0 -8 3.73
Thalamus L -12 -12 16 3.95
R 4 -20 8 3.62
Mesencephalon L -12 -30 -14 4.45
R 8 -28 -8 3.23
Cerebellum L -30 -42 -42 4.18

Traits
Middle frontal gyrus L -36 12 36 4.68
Thalamus L -10 -8 2 2.93
R 8 -4 6 3.29
Caudate L -16 0 16 4.19
R 18 -4 20 3.55
Pallidum/ Putamen L -20 -4 -2 3.31
Cerebellum L -18 -68 -40 3.07
R 30 -64 -36 4.21

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Table 2.13. Brain activity for self and participants’ Body Awareness Questionnaire (BAQ)
scores. Coordinates (x, y, z; MNI-152 standard space) and Z-scores correspond to the activation
peaks (clusters Z > 2.3; cluster probability p < .05) negatively correlated with participants’ BAQ
scores.

Structure

H

x

y

z

Z

Facts
Medial prefrontal cortex/anterior cingulate cortex

L
-2 32 28

3.76
R 2 18 36 4.98
Posteromedial cortex L -12 -58 42 4.74
R 2 -56 64 3.719
L -12 -58 42 4.74
Middle frontal gyrus L -42 56 16 3.67
Inferior frontal gyrus L -46 38 6 3.56
Angular gyrus R 54 -24 34 3.95
Superior temporal gyrus R 62 16 -8 3.94
Insula L -38 8 -4 3.21
R 36 -2 -8 2.98
Putamen/ Pallidum/ Caudate L -20 4 -2 3.83
R 18 6 4 4.33
Fusiform gyrus L -32 -46 -16 3.82
Cerebellum L -14 -64 -24 3.46
R 22 -68 -22 3.74

Traits
Posteromedial cortex L -10 -70 42 3.83
Superior parietal lobule L -22 -74 48 4.5
Superior parietal lobule/ angular gyrus L -38 -52 46 3.54
Insula L -26 22 -4 3.05
Putamen/ pallidum L -20 -2 0 3.82
R 22 4 4 3.72
Thalamus L -10 -12 0 3.76
R 12 -6 6 3.14
Mesencephalon L -10 -22 -16 3.56
R 4 22 -12 3.42
Cerebellum L -26 -50 -36 4.25
R 42 -62 -34 4.89

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Table 2.14. Brain activity for traits > facts and participants’ Body Awareness Questionnaire
(BAQ) scores. Coordinates (x, y, z; MNI-152 standard space), and Z-scores correspond to the
activation peaks (clusters Z > 2.3; cluster probability p < .05) positively correlated with
participants’ BAQ scores.

Perspective taking (PT). Participants’ PT scores correlated positively with signal for other
conditions, as follows: for other-facts, bilaterally in the medial prefrontal cortex, anterior
cingulate cortex, frontal pole, precentral and superior frontal gyri, and in the left thalamus and
putamen; for other-traits, bilaterally in the cerebellum (Table 2.15).

Structure

H

x

y

z

Z

Self –traits > self-facts
Angular gyrus R 66 -28 26 4.02
Insula R 40 -22 0 3.17

Other-traits > other -facts
Posteromedial cortex L -2 -62 60 4.51
R 6 -66 64 4.29

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Table 2.15. Brain activity for other and participants’ Perspective Taking (PT) scores. Coordinates
(x, y, z; MNI-152 standard space) and Z-scores correspond to the activation peaks (clusters Z >
2.3; cluster probability p < .05) positively correlated with participants’ PT scores.

Structure H x y z Z

Facts

Medial prefrontal cortex/ anterior cingulate cortex L -10 54 10 3.58
R 8 30 60 3.59
Frontal pole L -44 42 12 3.83
R 42 54 0 4.11
Precentral gyrus/
Superior frontal gyrus
L
-20 12 58

3.48
R 34 -10 44 4.07
Thalamus/ putamen L -20 -10 12 3.95

Traits

Cerebellum L -8 -44 20 3.71
R 6 -42 18 3.69

Empathic Concern (EC). No statistically significant correlations were found between
participants’ EC scores and brain activity for other-conditions.

Acquaintanceship length. Participants’ acquaintanceship lengths correlated positively
with signal for other conditions, as follows (Table 2.16):
(i) for other-facts, in the right insula, postcentral gyrus and superior temporal sulcus;
(ii) for other-traits, bilaterally in the medial prefrontal cortex, superior and middle
frontal gyri; and right anterior cingulate cortex, orbitofrontal cortex, inferior
frontal gyrus, precentral gyrus, basal forebrain and insula.

88

Table 2.16. Brain activity for other and participants’ acquaintanceship lengths. Coordinates (x, y,
z; MNI-152 standard space) and Z-scores correspond to the activation peaks (clusters Z > 2.3;
cluster probability p < .05) positively correlated with participants’ acquaintanceship lengths.

Structure

H

x y z Z

Facts
Insula R 38 -30 14 4.12
Postcentral gyrus R 54 -6 26 4.38
Postcentral gyrus/
Superior temporal sulcus
R
60 -24 18

3.91

Traits

Medial prefrontal cortex L -4 58 30 4.76
R 4 54 16 3.13
Anterior cingulate cortex R 4 32 28 3.03
Orbital frontal cortex/ basal forebrain R 28 30 -24 4.24

Superior frontal gyrus L -42 48 20 4.48
R 20 44 40 5.18
Middle frontal gyrus L -40 50 22 4.48
R 52 16 38 3.58
Inferior frontal gyrus R 52 24 10 3.81
Postcentral gyrus R 50 -12 36 4.04
Insula R 40 -6 6 3.62

Descriptiveness similarity. Participants’ descriptiveness similarity scores correlated
positively with signal in the right lateral occipital cortex (MNI coordinates: 40, -70, 22; Z-score =
3.66) for other-facts; and negatively with activity for other-traits bilaterally in the superior and
middle frontal gyri, and temporal pole; and in the right inferior frontal gyrus (Table 2.17).

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Table 2.17. Brain activity for other-traits and participants’ descriptiveness similarity scores.
Coordinates (x, y, z; MNI-152 standard space) and Z-scores correspond to the activation peaks
for other-traits (clusters Z > 2.3; cluster probability p < .05) negatively correlated with
participants’ acquaintanceship length.

Structure H x y z Z

Superior frontal gyrus
Middle frontal gyrus
L
38 48 24

3.77

R 8 54 46 4.08
Inferior frontal gyrus R 54 28 4 3.76
Middle temporal gyrus/Temporal pole L -44 10 -38 4.48
R 44 28 -32 4.93

Discussion
Our results show that, both for self and other, evaluative tasks regarding the two domains
of information generated greater activity in CMSs compared with baseline. Moreover, the four
experimental conditions engaged regions related to semantic memory (e.g., Binder et al., 2009),
autobiographical and episodic memory (e.g., Cabeza & Jacques, 2007), and somatic
representations related to emotion and decision-making (e.g., Nakao et al., 2012). These results
support that CMSs activity during evaluative tasks of biographical information relates to
processes of memory retrieval and decision underlying the tasks, for both self and other. In the

90
paragraphs below, I discuss the relevant findings with respect to autobiographical self processes,
the distinction of self versus other, and the role of cortical midline structures.

Autobiographical self
The autobiographical self state requires access to memories that are stored over a lifetime
of experiences. The process, however, is not likely to stop at memory retrieval. Once retrieved,
such memories may trigger emotional reactions and produce further retrieval of related memories.
Consequently, an autobiographical self state may range from relatively simple, as when one
displays landmark facts relative to one’s date and place of birth, to fairly more complex, as when
one is asked to describe a specific event or period of one’s life (Damasio, 1998). Our results
support these assumptions. As noted earlier, however, the experimental task appears to require
both memory retrieval and decision processes, indicating that the latter needs also to be
considered.

Autobiographical-self states vary with the domain of information that is being
processed.
The data I obtained demonstrate that evaluating autobiographic information varies
according to the domain of information. The reaction times to the questions were shorter for self-
facts than for self-traits. This advantage suggests that both memory and decision processes are
more straightforward for facts than for traits. As explained before, given the relevance of facts
regarding one’s identity in daily life, it is possible that individuals hold less ambiguous and more
objective (summarized) memory representations for biographical facts than for traits. This

91
possibility is supported by the results showing that mean ambivalence scores were greater for
facts than for traits.
Compared with self-traits, self-facts were associated with greater activity in PMC, MPFC,
hippocampus and basal forebrain. This is probably due to the processes of retrieval given the role
of these structures in memory (e.g., Binder et al., 2009) and may indicate that questions about
facts triggered greater amount of memory retrieval than the questions about traits. I note that the
questions were presented for 4 seconds in blocks of 24 seconds and thus this greater activity
might even be due to retrieval of additional memories occurring after the questions are answered
rather than to the retrieval needed to answer the questions in the first place. In any case, as
discussed above, the number of daily events and experiences regarding one’s facts is probably
greater than that regarding one’s traits, and thus an individual is likely to hold a greater amount of
memories for facts than for traits. Nonetheless, it is possible that this activity relates not only to
the amount of memories retrieved but also to aspects pertaining to the kind of the memories
retrieved, such as the age of those memories. Specifically, because facts are especially relevant to
one’s everyday life, they may be preferentially associated with recent memories. I know that
recent memories compared with past memories are associated with greater activity in the PMC
(D’Argembeau, et al., 2008; Gilboa et al., 2004; Soderlund et al., 2011) and in the MPFC
(D’Argembeau, et al., 2008).
Self-traits were associated with greater activity in the anterior insular cortices than self-
facts. Given that the role of the insular cortices in somatic representations and in feeling states is
well established (reviewed in Damasio and Carvalho, 2013), this finding may suggest that,
compared with facts, traits elicited greater amount of emotion-related representations. These
representations may occur as responses to the memories retrieved or to processes of decision-

92
making, such as error monitoring and conflict solving during decision-making (Orr & Hester,
2012). Furthermore, these responses are likely to be greater for traits than for facts because of the
greater emotional significance of traits. I know, for example, that traits vary in valence and
desirability (Anderson, 1968), and individuals seem to prefer to be associated with socially
desirable traits, as the data on descriptiveness demonstrate and other authors have also noted
(Klein & Loftus, 1993). Furthermore, as indicated above, the representations for traits are more
likely to be ambivalent than those for biographical facts and thus traits, compared with facts, may
be associated with less straightforward decision-making processes.

Autobiographical-self states vary with the specific information that is being processed.
Our results showed that the level of brain activity in relevant structures such as the PMC
and the MPFC correlated with participants’ ambivalence scores (i.e., how close participants’
ratings were descriptiveness were close to fully descriptive or to fully non-descriptive) and with
participants’ importance scores. In other words, the level of activity in CMSs seems to be lower
for individuals who considered the information unambivalently descriptive or non-descriptive and
are thus likely to have required lower level of processing related to memory retrieval and decision
making.
In addition, the level of activity in the MPFC was also lower for individuals who
considered the traits more important to their self-image, and thus probably have given prior
consideration to the information requiring lower level of processing relate to memory retrieval
and decision making to answer the questions. These individuals also engaged less activity for
traits in structures related to emotional processing such as anterior cingulate and the insula, which
seems to support the notion that traits are associated with emotional reactions.

93
Last, the participants who reported having retrieved greater amount of episodes to answer
the questions seemed to require greater levels of activity in the structures related to memory
retrieval, such as the PMC.
Altogether, these results seem to support the notion that brain activity for evaluation of
biographical information varies across individuals, depending on the level of processing related to
memory retrieval and decision making required to answer the questions.

Autobiographical-self states vary with personality differences for how self information
tends to be processed
The results seem to confirm that individuals who tend to think more about themselves
(higher SCS scores) were associated with greater level of activity generated during self-traits and
self-facts in several brain regions, including CMSs and emotion-related areas (e.g., insula),
compared with individuals who tend to less about themselves (lower SCS scores). This appears to
support that the level of processing (related, for example, with memory, thoughts and reasoning)
involved in the autobiographical self states elicited by questions varies with one’s personality.
This is further supported by the finding that participants’ estimated number of memories for self-
facts correlated positively with SCS scores in this study.
Intriguingly, the data revealed also that individuals who hold greater tendencies for
conscious processes related to body changes (higher BAQ scores) were associated with lower
levels of activity in CMSs and somatic-related areas (e.g., insula) compared with individuals who
hold lower tendencies in the same regard. Nonetheless, the difference between traits and facts in
terms of activity in the insula correlated positively with participants’ BAQ scores. This finding

94
seems to support the hypothesis that participants with higher BAQ scores are associated with
greater level of emotion-related somatic processing during the evaluation of traits.
Altogether, these findings support the notion the scope and the nature of processing
involve in autobiographical self states depend on personality differences related to how one’s
tends to process self-related information.

Self versus Other
Evaluating information pertaining to others is similar to evaluating self-related
information.
Our data on the comparison of each condition with the baseline support the proposal that
self and other engage some of the same structures, including CMSs. This is consistent with the
proposal that two processes required to evaluate biographical information – memory retrieval and
decision-making – are comparable for self and for other. Similarly to what I observed for self,
brain activity related to other appears to vary with the domain of information evaluated (traits
versus facts), as well as with individual differences on descriptiveness (how well the information
targeted by the questions described other), and estimates of amount of memory retrieval that was
required to answer the questions.

Evaluating information pertaining to others requires longer time, more memory
retrieval and greater level of CMSs activity
The results also reveal intriguing differences between self and other. Compared with
other, self was associated with shorter reaction times, smaller perceived amount of memory
retrieved, and lower levels of activity in CMSs’ integrative hubs such as the PMC. These

95
significant differences were probably influenced by the choice of other, and relate to differences
regarding the type and accessibility of the memories between self and a distant other.
Autobiographical memories derive from a multitude of instants of self-knowledge distributed
over a person’s lifetime. Consequently, the amount of autobiographical memories is predictably
very large. Moreover, individuals also form abstract summary representations from some of those
autobiographical memories (Klein & Loftus, 1993). On the other hand, as explained before, the
representation of a distant acquaintance’s biography derives from events and experiences that
may have occurred during limited interactions over the course of the acquaintanceship. Thus
memories for a distant acquaintance are probably less numerous, less frequently retrieved, and
less readily accessible than autobiographical memories. In addition, it is likely that individuals are
less likely to hold summary representations for a distant acquaintance (Fuhrman & Funder,
1995). Our data on the ambivalence scores and importance ratings seems to support this view. I
note, however, that individuals’ knowledge of other may be similar to that of self when the other
is a close acquaintance (Fuhrman & Funder, 1995), possibly explaining discrepancies of among
the published results.
Unlike what was observed for self, other-traits compared with other-facts were not
associated with greater insula activity. Considering the association of the insula with affective
processing, this difference suggests that emotion-related somatic representations are more
prominent for self than for a distant other. This finding too may be explainable by the choice of
other used in this study. Given the lack of a close relationship between the participants and the
acquaintances, the emotional significance of the retrieved memories and of the related decision-
making is possibly smaller for other than for self. Of note, although positive traits were
considered more descriptive than negative traits for both self and other, the difference was greater

96
for self than for other. Also, positive traits were considered more important than negative traits
for self but not for other. A recent meta-analysis of studies of self-reference, many of which
explored the domain of personality traits, also suggests that self is associated with greater activity
in the insula than other (Qin et al., 2011).

Evaluating information pertaining to others depends on personality measures related to
how information pertaining to others tends to be processed
The results showed that the level of brain activity, including in the ACC and MPFC, for
other facts was commensurate with participants’ PT scores. Because the ACC and the MPFC has
been shown to be involved in emotion processing (Etkin, Egner, & Kalisch, 2011), this result
suggests that the level of emotional responses to other-facts was greater for participants with
greater tendencies to assume another person’s perspective than for those with lower tendencies in
that regard. In addition, it supports the notion that brain activity generated for another person
depends on personality measures related to how one tends to process other-related information.

Evaluating information pertaining to others depends on who the other is relation to self
The level of brain activity generated for other-facts and other-traits in memory related
regions (e.g., the basal forebrain) as well as in emotion related regions (e.g., insula) correlated
positively with participants’ acquaintanceship lengths. This suggests that, during the evaluation
of an acquaintance’s traits and facts, participants who knew their acquaintances for longer
showed greater level of memory retrieval and emotion-related processing than participants who
knew their acquaintances for shorter periods of time.

97
It is likely that the length of an acquaintanceship is commensurate with number of
experiences with an acquaintance. Consequently, individuals may well hold a greater number of
experiences and related memories for acquaintances they know for longer than for those they
know for shorter periods of times.
Likewise, the length of an acquaintanceship may be also commensurate with the level of
emotional processing associated with reflecting on an acquaintance. This may be explained by the
likely possibility that longer acquaintanceships tend to be affectively stronger than shorter
acquaintanceships. Intriguingly, in this study, however, the participants were instructed to choose
a distant acquaintance with whom they did not have a strong emotional connection. It is possible
that level of emotional processing during other-conditions found in this study did not relate to the
degree affective closeness with the acquaintance, but rather to the number of the experiences
involving the acquaintance. In other words, longer acquaintanceships may be associated with
greater emotional processing because they tend to be associated with greater number of
experiences involving the acquaintance, as discussed above.

Cortical Midline Structures
Overall, the results confirm that CMSs are involved in processes of self. Nonetheless, the
involvement also occurs for other. Moreover, the level of activity in CMSs appears to increase for
conditions requiring greater level of processing related to memory retrieval and decision-making.
Still, the data also suggest that there are functional differences for subcomponents of the CMSs,
namely between the MPFC and the PMC.
The MPFC is connected with structures involved in memory processing, such as the
hippocampus, as well as with structures involved in somatic representations related to emotions,

98
such as nuclei in the brainstem tegmentum, amygdala and cingulate cortex (reviewed in Fuster,
2008). It has been suggested that the MPFC is also engaged in the integration of emotion-related
somatic signals in decision-making (Bechara et al., 2000). Our data seem to support this
suggestion, by showing the activity in the MPFC correlated negatively with ambivalence and
importance, which are presumably commensurate with how straightforward the decision-making
processes were. Data from a more recent study showed also that activity in the MPFC during
traits correlated positively with the decision difficulty (Meffert, 2013).
It is possible that activity in the MPFC relates also to memory retrieval, particularly to
processes of emotional and perceptual representations related to the retrieved memories. Such
processes could contribute, for example, to a “felt-rightness” during memory retrieval, as
proposed in Moscovitch & Winocur, 2002. Our data regarding the difference between facts and
traits support this idea, given that facts compared with traits are, as noted before, likely to be
associated with greater amount of autobiographical memories and even greater amount of recent
memories. Other results are in line with this view: (i) high-experience domains of autobiographic
information compared with low-experience domains of autobiographical information engage
greater activity in MPFC, nucleus accumbens and amygdala (Lieberman et al., 2004); (ii) current
autobiographical information compared with past autobiographical information involves greater
activity in the MPFC (D’Argembeau et al., 2008); and (iii) activity in the MPFC correlates with
the participants’ success in retrieving information that pertains to self (Macrae et al., 2004) and to
non-self (Schnyer et al., 2005).
MPFC activity for other probably depends on the same factors, which are likely to be
strongly influenced by who the other is in relation to self. Our data demonstrated that MPFC
activity was commensurate with participants’ PT scores, and with acquaintanceship length. In

99
addition, data from other studies appear support this view. For example, activity in the MPFC is
not different for self and for a close friend, but it is greater for self than for a distant other
(Ochsner et al., 2005). Along the same lines, the difference in MPFC activity between self and
the participant’s mother has been shown to depend on the participants’ cultural background (Zhu
et al., 2007).
The PMC has been shown to be a central hub of cortical connectivity (e.g., Hagman et al.,
2008; Parvizi et al., 2006). It seems to be engaged by integrative general-purpose processes
(reviewed in Damasio, 2010). Its activity correlates with the state of awareness. For example, it
increases gradually as coma progresses to vegetative stage and to full awareness (Laureys et al.,
2004). During the evaluation of biographical information, the PMC is likely to be particularly
involved in retrieving and assembling memory fragments. The PMC is severely compromised in
Alzheimer’s disease, Wernicke-Korsakoff’s amnesia and post-anoxic amnesia (Laureys et al.,
2004), and is engaged by memory tasks, pertaining to autobiographical and non-autobiographical
information (e.g., Binder et al., 2009). Furthermore, as noted above, PMC activity is greater for
other compared with self, and for facts compared with traits. This is consistent with recent meta-
analyses that show greater activity in PMC for other compared with self (e.g., Araujo et al., 2013;
Qin et al., 2011). In addition, PMC activity correlates negatively with ambivalence scores for
traits, and positively with estimates of amount of memory retrieved for facts, supporting the view
that the PMC’s involvement in memory is commensurate with memory effort, memory load or
both. Data from other studies support this interpretation. The PMC has been shown to be more
active (i) during recall of recent memories, either real or fictitious, than recall of recently seen
objects (Hassabis et al., 2007), (ii) during recall of information than repetition of information
(Buckner et al., 1996; Schacter et al., 1996), (iii) during recall of a greater number of words than

100
recall of a smaller number of words (Schacter et al., 1996), and (iv) during processing of recent
memories than processing old memories (Gilboa et al., 2004, Soderlund et al., 2011).

Conclusion
The level of activity in CMS during the performance of tasks designed to evaluate
biographical information seem to depend on varied factors related to the memories elicited by the
questions, and to the processes of decision-making required to answer the questions. The
evidence does not support the notion that autobiographical self processes depend first or mostly
on CMSs, or that the CMSs are specifically devoted to self-related processing. The results are
compatible with the notion that CMSs are hubs capable of assisting different processes, ranging
from those that occur during resting states (e.g., mind wandering), to those that underlie the
evaluation of biographical information.

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Chapter 3
Contrasting brain activity for core-self and autobiographical-self mental states

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Abstract
Self-related mental states may focus on historical aspects of one’s life (autobiographical
self) or one’s ongoing body state, such as sensations pertaining to one’s internal milieu (core
self). The neural substrates behind those mental states have not been fully elucidated, although
brain structures such as the midline and insular cortices have been linked to processing some
domains of information related to self.
Here, I contrasted brain activity for two domains of core-self information (interoception
and exteroception) and two domains of autobiographical-self information (personality traits and
biographic facts). In addition, I explored how brain activity for the experimental conditions
varied across the participants in relation to the specific information targeted in the questions, as
well as in relation to personality measures pertaining to how self-information tends to be
processed.
This was a block-design fMRI study, involving 19 participants who answered questions
about each domain of information (4 experimental conditions). After being scanned, the
participants rated the information targeted by each question in terms of descriptiveness and
importance; they also estimated the amount of memory retrieved to answer the autobiographical
self questions, and the amount of memory retrieval that was elicited by the core self questions. In
addition, the participants filled personality questionnaires regarding how self-related information
tends to be processed, namely: (i) the Self -Consciousness Scale, Body Awareness Questionnaire,
Body Perception Inventory, and Multidimensional Inventory of Hypochondriacal Traits.
The four conditions appeared to involve varied brain regions, including midline and
insular cortices. Activity in body-related and memory-related regions was observed in all
conditions, but body-related regions showed greater activity for core self than for

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autobiographical self; memory-related regions on the other hand yielded greater activity for
autobiographical self than for core self. In addition, activity generated for the conditions varied
with differences across the participants in relation to the specific information targeted by the
questions (descriptiveness, importance and memory estimates) as well as their personalities.
I regard these results as an indication that the mental states elicited by self-related
questions are rather complex and do not involve solely regions that are functionally dedicated to
processing the information targeted by the questions.

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Introduction
The mental states generated when individuals retrieve memories for historical aspects of
their lives contribute to what has been designated as the autobiographical self (Damasio, 1998).
The autobiographical self permits conscious access to one’s relatively stable biographical
information, including simple facts of one’s identity (e.g., date of birth), personality traits (e.g.,
honesty), as well as specific life events and episodes (e.g., one’s high school graduation). On the
other hand, the mental states that allow individuals to form a conscious account of their ongoing
body state contribute to what has been designated as the core self (Damasio, 1998). The core self
relates to interoceptive body changes (e.g., hunger, thirst, or fatigue), and to a class of
exteroceptive changes caused by the interaction of the body with the outside world (e.g., pressure
exerted on one’s arm).
The neural substrates for these two states – autobiographical self and core self – have not
been satisfactorily elucidated. There is evidence, however, that cortical midline structures
(CMSs), particularly the medial prefrontal (MPFC) and posteromedial (PMC) cortices, are
engaged when individuals examine aspects of their personalities or their identities ((Northoff &
Bermpohl, 2004), suggesting that CMSs play a role in autobiographical self mental states. Still,
existing studies indicate that CMSs are not dedicated to autobiographical self states and assist a
wider range of internally oriented processes (Araujo et al., 2013). Moreover, the CMSs are highly
connected to cortical and subcortical regions related to processing body information (Hagmann et
al., 2008; Parvizi, van Hoesen, Buckwalter, & Damasio, 2006). It is thus important to investigate
how activity in CMSs differs for autobiographical self and core self.
Looking beyond the CMSs, it has also been shown that the insular cortices are involved in
processing varied body sensations, especially those related to interoception (Craig, 2002), raising

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the possibility that the insula plays a role in generating core self states. But there is also evidence,
albeit more limited, that the insula is involved in memory retrieval (Singer, Critchley, &
Preuschoff, 2009) and in evaluating one’s personality traits (Modinos, Ormel, & Aleman, 2009),
raising the possibility that the insular cortices also contribute to autobiographical self mental
states. As in the case of CMSs, it is important to determine how the involvement of the insula
differs for autobiographical self and core self.
In the current study, I investigated the role of these brain structures in core and
autobiographical self processes by conducting an fMRI study in which participants were asked to
answer questions about themselves. The questions required that the participants examined aspects
related to their ongoing body status (mental states pertaining to the core self), or aspects related to
their personality and biography (mental states pertaining to the autobiographical self). In the hope
of ensuring that participants would disengage from self-related examination during baseline, I
used an active baseline consisting of periods of one-back task in a block design.
The core -self questions were organized into two experimental conditions, according to
the domains of body sensations targeted by the questions: (i) the internal milieu, “interoception”
(e.g., “Are you hungry?”); or (ii) skin contact with external stimuli, “exteroception” (e.g., “Can
you feel anything touching your arm?”). Both conditions required that individuals examine their
ongoing body status, but distinct core self domains were targeted because there are substantial
physiological differences between interoception and exteroception (Ref. Book).
The autobiographical self questions were also organized into two conditions, one
concerning personality traits (“traits”; e.g., “Does the word honest describe you?”); another,
critical biography and identity facts (“facts”; e.g., “Are you a student?”). In both conditions,
individuals needed to examine historical aspects of themselves, but each condition focused on a

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separate domain of autobiographical self given that personality traits and biographical facts are
distinct (Keenan, Golding, & Brown, 1992). Personality traits vary in valence and desirability,
whereas biographic facts do not. Moreover, the examination of one’s personality traits is
relatively subjective because it depends on personal judgments of a set of experiences, while the
examination of one’s biographical facts is largely objective because such facts tend to be
incontrovertible and verifiable.
I explored how brain activity for the experimental conditions varied across the
participants in relation to the specific information targeted in the questions, as well as in relation
to personality measures pertaining to how self-information tends to be processed (Figure 3.1).
For the autobiographical-self conditions, the differences between the participants
regarding how information being processed were estimated using the same measures used in
Chapter 2, as follows: (i) descriptiveness (i.e., the ratings of how well the content of the questions
described the participants); (ii) importance (i.e., how important the content of the questions was
to address the participants’ self-image); and (iii) amount of memory retrieved to answer the
questions (i.e., the participants’ estimates of number of episodes retrieved to answer the
questions).
For the core-self conditions, similar measures were used to assess differences between the
participants regarding the body sensations being processed: (i) descriptiveness (i.e., the ratings of
how well the body sensations targeted by the questions described the participants’ ongoing body
status at that moment); (ii) importance (i.e., how important the body sensations targeted by the
questions tend to be to the participants); (iii) amount of memory elicited by the questions (i.e., the
participants’ estimates of number of episodes retrieved that were elicited by the questions).
In addition, personality differences across the participants were collected using the

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following scales/questionnaires:
(i) the Self -Consciousness Scale (SCS) which assesses a person’s tendency to reflect on
oneself (e.g., “ I’m always trying to figure myself out.”) (Scheier & Carver, 2005);
(ii) the Body Awareness Questionnaire (BAQ) , which measures a person’s tendency to
notice body sensations (e.g., “I notice specific bodily reactions to being over-
hungry.”) and to predict body-related processes (e.g., “ I can tell in advance when I go
to bed how well I will sleep that night.”) (Shields, Mallory, & Simon, 1989);
(iii) the Awareness - Body Perception Inventory (Awareness –BPI), which is part of the
Body Perception Inventory (BPI) and assesses one’s tendency to notice body
sensations (e.g., “ During most situations, I am aware of swallowing”) (Porges, 1993);
(iv) the Autonomic Reaction - Body Perception Inventory (Autonomic Reaction –BPI),
which is part of the BPI, and measures one’s tendency to experience body changes
predominantly related to the autonomic nervous system (e.g., “I feel nauseated.”)
(Porges, 1993);
(v) the Absorption- Multidimensional Inventory of Hypochondriacal Traits (Absorption –
MIHT), which is part of the Multidimensional Inventory of Hypochondriacal Traits
(MIHT) and assesses one’s hypersensitivity to body changes (e.g., “Even when I
listen to lecture or a talk, I am alert to how my body feels.”) (Longley, Watson, &
Noyes, 2005);
(vi) the Worry - Multidimensional Inventory of Hypochondriacal Traits (Worry – MIHT),
which is also part of the MIHT, and assesses one’s tendency to worry excessively
about illness and health (e.g., “I worry a lot about my health.”) (Longley et al., 2005).

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Figure 3.1. A. Experimental conditions used in the fMRI study. The conditions varied according
to whether the questions targeted autobiographical self domains, either about biographic facts or
about personality traits; or targeted core self domains, either in relation to one’s internal milieu
(“Interoception”) or in relation to body changes occurring in relation to external world
(“Exteroception”). B. Between-subject variables used in this study. These variables were
collected after scanning the participants, and included participants’ ratings regarding
“importance”, “descriptiveness”, and retrieved memory for each condition; and measures of their
personalities: (i) Self –Consciousness Scale, SCS; (ii) Body Awareness Questionnaire (BAQ);
(iii) Awareness – Body Perception Inventory (BPI); (iv) Autonomic – BPI; (v) Absorption -
Multidimensional Inventory of Hypochondria Traits (MIHT); (vi) Worry – MIHT.

(vii) A. Experimental conditions

B. Between-subject variables

For each condition Core self

Interoception

Exteroception

Importance

Descriptiveness

Memory

Autobiographical self Personality differences

Biographic
facts

Personality
traits

Self-image
related:

SCS

Body –
processing
related:
BAQ

Awareness –
BPQ

Autonomic
reaction -BPQ

Hypochondria
–related:

Absorption-
MIHT

Worry -MIHT

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I hypothesized the following:
1. Compared with autobiographical self conditions, core self conditions require more
extensive processing of body-related representations and are associated with a greater
level of activity in body-related regions, such as the somatosensory cortices and
insular cortices. Although autobiographical self conditions can be associated with
some processing of body-related representations, such processing relates
predominantly to emotional responses elicited by memory retrieval and decision
processes required to answer autobiographical self questions, and is thus associated
with activity in regions supporting emotion-related somatic representations, such as
the insular and anterior cingulate cortices.
2. Compared with core self conditions, autobiographical self conditions require greater
memory retrieval and are associated with greater level of activity in memory-related
regions, such as the hippocampus and anterior temporal cortices. Still, core self
conditions are likely to elicit some memory retrieval, and thus are associated with
activity in memory-related regions but to a lesser extent and degree.
3. CMSs are involved in both core self and autobiographical self processes, but their
involvement is greater for autobiographical self conditions than for core self
conditions because the level of processing of internally generated representations is
likely to be greater for memories than for body sensations. Memory retrieval is an
elaborative process and requires assembling of a variable number of representations
for the different elements of a given memory. Even though the retrieval of certain
memories (e.g., semantic memories) may be relatively simple, retrieving a memory

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tends to elicit retrieval of related memories. Moreover, even relatively simple
memories are likely to be associated with varied imagery pertaining to different
sensorial modalities. On the other hand, although certain body sensations are
associated with relatively varied mental imagery, such as auditory imagery (e.g.,
shortness of breath) and visual imagery (e.g., pallor associated with nausea), the scope
of the imagery for body sensations is likely to be more limited (Critchley & Harrison,
2013).
4. Certain regions within CMSs, such as the cingulate cortex (Cameron, 2009) and the
superior part of the PMC (Parvizi et al., 2006), are more active for core self than for
autobiographical self because they are strongly connected with regions involved in
body processes. Moreover, the cingulate cortex is connected to brainstem nuclei
related to interoception (Cameron, 2009) and is thus possibly more active for
interoception than for exteroception. Likewise, the superior PMC is predominantly
linked to somatosensory, motor and premotor cortices (Parvizi et al., 2006), and is
more active during exteroception than during interoception.
5. As indicated above, the insular cortices are involved in core self and autobiographical
self states. Nonetheless, I predict that the anterior insula is more active for
autobiographical self states than for core self states; the reverse pattern applies to the
posterior insula. I based this prediction on findings that suggest that body-related
processing is relatively simple in the posterior insula and relates to “actual” body
changes, but it becomes increasingly more complex and related to processing of
affective responses in the anterior insular cortices (reviewed in (Craig, 2002; 2009).
6. Brain activity generated for autobiographical self conditions is likely to vary across

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individuals, as proposed in Chapter 2. In brief:
a. The level of CMSs activity for autobiographical self correlates negatively with
participants’ importance ratings and ambivalence scores, but it correlates
positively with participants’ memory estimates and SCS scores.
b. The difference of activity between traits and facts in terms of involvement of
regions supporting emotion-related somatic processes correlates positively
with participants’ scores for BAQ, Awareness-BPI and Autonomic Reaction-
BPI.
7. Brain activity generated for core self conditions is likely to vary across individuals, as
follows:
a. The level of body-related processing, and consequently the level activity in
brain regions related to body processing, correlates positively with
participants’ importance ratings, and their scores for BAQ, Awareness-BPI,
Autonomic Reaction-BPI, Absorption –MIHT, and Worry –MIHT.
b. The level of memory retrieval, and thus the level of activity in memory-related
brain regions, correlates positively with participants’ estimates of the amount
of memory elicited by core self questions.

Methods

Participants
Twenty participants (10 female, and 10 male; 22.5+/- 2.6 years old) were recruited from the
University of Southern California community. All participants were native English speakers,

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right-handed, with no history of neurological diseases. They were paid for their participation, and
provided written informed consent following the Institutional and Federal Guidelines. The data
from one of the participants were excluded because he was not able to read some of the
questions. The final study sample consisted of 19 participants (10 female, and 9 male; 22.6 +/-
2.6 years old).

Materials and Procedures
The experimental stimuli consisted of questions that varied according to four experimental
conditions: (i) traits, regarding one’s personality traits (e.g., “Does the word ‘honest’ describe
you?”); (ii) facts, regarding one’s biographical facts, such as demographic data (e.g., “Are you a
student?”); (iii) interoception, regarding sensations pertaining to internal aspects of one’s body
(e.g., “Are you hungry?”); (iv) exteroception, regarding sensations pertaining to external aspects
of one’s body (e.g., “Do your hands feel wet?”).
The questions about personality traits contained a selection of personality traits from a list of
personality traits rated in terms of likableness and meaningfulness by 100 college students
(Anderson, 1968). The selection included only adjectives with the highest meaningfulness scores
and equal numbers of negative traits (the least liked adjectives) and positive traits (the most liked
adjectives). The questions about biographic facts covered several aspects of one’s life, such as
age, height, weight, ethnicity, nationality, occupation, typical means of transportation, household
and physical appearance.
The questions about interoception involved interoceptive sensations related to one’s mouth,
nose and throat (e.g., ‘Is your throat OK?’), gastrointestinal system (“Does your stomach ache?’),
and heartbeat and respiratory movements, as well as questions related to absence or presence

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hunger or thirst (e.g., “Do you feel hungry?”). The questions about exteroception comprised
sensations regarding pressure, dryness or wetness, in relation to the neck and back, upper and
lower limbs (e.g., “Do your legs feel wet?”). The participants were instructed that questions
related to interoception and exteroception referred to current body sensations (i.e., sensations
occurring at the moment they read the question).
The baseline separating the blocks of questions consisted of periods of one-back task, during
which the participants saw a series of letters, one at a time, and had to decide whether each of the
presented letters was identical to the one immediately preceding it. All stimuli were presented
visually on a screen at the end of the scanner bore, viewed through a mirror placed on the head
coil. The participants responded to the stimuli by pressing a button with their right-hand fingers. I
used MATLAB (The Mathworks) and Psychophysics Toolbox Version 3 (The Psychophysics
Toolbox, 2001) for both the stimulus presentation and the response collection.
The study comprised three functional runs. Each run lasted 9.7 minutes and was organized in
a block-design, containing 3 blocks for each condition. A block lasted 24 seconds and included 6
questions. Each question was presented for 4 seconds. Blocks of questions were separated from
one another by a 24-second block of the one-back-task. The blocks were presented in a
randomized order for each run and each participant.

Questionnaires
Ratings and estimates. After the scanning, the participants estimated the number of
memories (e.g., particular episodes) they recalled in order to answer the questions for “traits’ and
for “facts”, using a 7-point Likert scale (1: I did not recall any particular memory.; 7: I recalled
many episodes…). In addition, they also estimated the number of memories (e.g., particular

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episodes) elicited by the questions for “interoception” and for “exteroception”, using a similar
scale.
The participants also rated the content of each question in terms of how well it described
them (self-descriptiveness) and of how important (self-importance) it was to their identities. For
these ratings, each question was transformed into a statement, (“You are a student.”), and Likert
scales were used. The scales ranged as follows: (i) for self-descriptiveness, from 1 (… definitely
untrue or uncharacteristic of me.) to 5 (…very true or strongly characteristic of me.); (ii) for self-
importance, from 1 (… definitely not important to my identity.) to 5 (… absolutely important to
my identity.); (iii) for other-descriptiveness, from 1 (… definitely untrue or uncharacteristic of
him /her.) to 5 (… very true or strongly characteristic of him /her.); (iv) for other –importance,
from 1 (… definitely not important to the image I have of him/her.) to 5 (… absolutely important
to the image I have of him/her). I note that in the case of the core-self questions, the participants
were instructed that descriptiveness referred to the scan time (i.e., whether a body sensation
targeted in a questions was descriptive of themselves when they answered that question).
As for the study described in Chapter 2, ratings of descriptiveness were recoded in order
to assess how ambivalent (descriptive ambivalence) the participants considered the questions, as
follows: ratings 5 and 1 were recoded into 0, ratings 4 and 2 were recoded into 1, and rating 3
was recoded into 2.
All participants answered the following questionnaires: (1) Self-Consciousness Scale
(Fenigstein, Scheier, and Buss, 1975); (2) Body Awareness Questionnaire(Shields et al., 1989);
(3) (iii) Body Perception Questionnaire (BPQ) (Porges, 1993), which included two scales of
interest, namely “Awareness –BPQ”, and “Autonomic Reaction – BPQ”; (iv) Multidimensional
inventory of hypochondrial traits (MIHT), which included two scales of interest, namely,

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“Absorption– MIHT”, and “ Worry –MIHT”).
All behavioral data analysis, including repeated measures ANOVA and Pearson
correlations, was conducted with PASW Statistics 18.0.

Image Acquisition
The magnetic resonance images were acquired with a 3-Tesla Siemens MAGNETON Trio
System. The acquisition of echo-planar images (EPI) was performed using the following
parameters: TR = 2000ms, TE = 25ms, flip angle = 90˚, 64 x 64 matrix, in-plane resolution 3.0
mm x 3.0 mm, 41 transverse slices, each 3 mm thick, and field of view covering the whole brain.
Each run consisted of 291 volumes. The acquisition of the structural images (T1-weighted
magnetization-prepared rapid gradient echo, MPRAGE) used the following parameters: TR =
1950 ms, TE = 2.3 ms, flip angle = 7˚, 256 x 256 matrix, 193 coronal slices, 1 mm isotropic
resolution.
Image processing and analysis
The functional imaging data were preprocessed, registered and analyzed with FSL (FMRIB's
Software Library, www.fmrib.ox.ac.uk/fsl). The preprocessing included the following steps: (i)
motion correction with MCFLIRT (Jenkinson et al., 2002); (ii) slice-timing correction with
Fourier-space time-series phase-shifting; (iii) non-brain removal with BET (Smith, 2002); (iv)
spatial smoothing with a Gaussian kernel of FWHM 5mm; (v) grand-mean intensity
normalization of the entire 4D dataset by a single multiplicative factor; (vi) high-pass temporal
filtering (Gaussian-weighted least-squares straight line fitting, with sigma = 50.0 s).
Each participant’s functional data were registered to the participant’s high-resolution
structural images (7 degrees of freedom) and to a standard space (MNI-152 atlas, 12 degrees of

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freedom) using the FMRIB's Linear Image Registration Tool (FLIRT) (Jenkinson & Smith, 2001;
Jenkinson, Bannister, Brady, & Smith, 2002) and the FNIRT nonlinear registration (Andersson,
Jenkinson, & Smith, 2007a; Andersson, Jenkinson, Smith, & Andersson, 2007b).
The analysis of each participant’s functional data was performed using FSL's implementation
of the general linear model, FEAT (FMRI Expert Analysis Tool, Version 5.98). The model
included motion parameters and a separate regressor for each condition: traits, facts,
interoception, and exteroception. Each regressor derived from the convolution of the
corresponding task design and a double gamma function (representing the hemodynamic
response). Time-series statistical analysis was conducted with FILM using a local autocorrelation
correction (Woolrich, Ripley, Brady, & Smith, 2001).
For each participant, the functional data from three runs were then analyzed with a fixed-
effect model, which forces the random effects variance to zero in FLAME (FMRIB's Local
Analysis of Mixed Effects) (Beckmann, Jenkinson, & Smith, 2003; Woolrich, Behrens,
Beckmann, Jenkinson, & Smith, 2004).
The data from all the participants were analyzed using a mixed-effect model, FMRIB's Local
Analysis of Mixed Effects (FLAME) (Beckmann et al., 2003; Woolrich et al., 2004). For the
whole-brain analysis, a threshold was applied to all statistical images, using clusters determined
by Z > 2.3 and a corrected cluster size significance threshold of p = .05 (Worsley, 2001). In order
to identify regions commonly activated by the conditions, I performed conjunction analyses for
higher-level contrasts using easythresh_conj script in FSL (Nichols, 2007), the whole-brain as a
mask and a threshold of Z > 2.3, p = .05.
Hoping to help visualize the differences of activation in CMSs across the conditions, I also
determined mean parameter estimates (PE) for each condition-minus-baseline in masks for

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regions of interest (ROIs) in CMSs. The ROI masks consisted of spheres with 5-mm radius and
were centered on peaks of activation for the varied contrasts explored in the study (Table 3.11).
For each ROI, parameter estimates (PE) for each condition minus baseline in whole-brain
analysis were determined using FEATQUERY in FSL, and mean PE and standard error mean
(SEM) PE were calculated.
In order to explore the relationship between the behavioral co-variables and brain activity,
additional higher group analysis were performed, using a mixed-effect model, FMRIB's Local
Analysis of Mixed Effects (FLAME) (Beckmann et al., 2003; Woolrich et al., 2004), as follows:
(i) for each condition, participants’ mean importance and mean descriptiveness
ambivalence scores;
(ii) for self-traits and for self-facts (separate analyses), participants’ estimates of memory
retrieved to answer the questions;
(iii) for interoception and exteroception (separate analyses), participants’ estimates of
memory elicited by the questions;
(iv) for each condition, participants’ SCS scores;
(v) for each condition, and for the contrasts core-self > autobiographical-self and traits >
facts, (separate analyses), participants BAQ, “Awareness-BPI”, “Worry –BPI”
(vi) for each core self condition, and for the contrasts core-self > autobiographical-self
“Absorption-MIHT” and “Worry-MIHT”.
As before, a threshold was applied to all statistical images, using clusters determined by Z
> 2.3 and a corrected cluster size significance threshold of p = .05 (Worsley, 2001). Reaction
time data were analyzed using PASW Statistics 18.0.

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Results
Behavioral Data
Reaction times. Questions regarding autobiographical self were answered faster (M =
1.43 SEM = 0.04 s) than those regarding core self (M = 1.70, SEM = 0.07 s), F (1, 19) = 31.46, p
< .0001. In addition, reactions times were shorter for questions about interoceptive information
(M = 1.57, SEM = 0.06 s) than for those about exteroceptive information (M = 1.84, SEM = 0.07
s), F (1,19) = 55.69, p < .0001.
Importance ratings. Participants considered information targeted by autobiographical-
self questions (i.e., facts and traits) more important (M = 3.1; SEM = .126) to their self-images
than the sensations targeted by core-self questions (M = 1.68; SEM = .135), F= (1,19) = 102.11, p
< .0001. In addition, they considered traits (M = 3.54; SEM = .16) more important than facts (M
= 2.27; SEM = .125), F (1,19) = 40.49, p < .0001.
Ambivalence scores. The ambivalence scores for facts (M = 0.15; SEM = .024) were
smaller than those for traits (M = 0.52; SEM = .05), F= (1,19) = 58.57009, p < .0001; those for
interoception M = 0.41; SEM = .078), F= (1,19) = 12.783, p < .002; and those for exteroception
M = 0.46; SEM = .107), F= (1,19) = 12.033, p < .003.

Table 3.1. Mean reaction times, ambivalence scores (ranging from 0 to 2), and importance
ratings (ranging from 1 to 5) for the conditions.

Reaction Times Ambivalence Importance

Condition M SD M SD M SD

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Core self
Interoception 1.57 .066 0.41 .078 1.89 .164
Exteroception 1.84 .074 0.46 .107 1.47 .126

Autobiographical self
Facts 1.42 .045 0.15 .024 2.67 .125
Traits 1.44 .042 0.52 .05 3.54 .16

Memory. There were not statistically significant difference between traits and facts in
terms of the amount of episodes to answer the questions (facts: M = 3.21, SEM = .371; traits: M =
3.0; SEM = .286). In addition, participants reported that questions about interoception elicited
retrieval of greater amount of memory episodes (M = 2.32, SEM = .306) than questions about
exteroception (M = 1.68; SEM = .254), F (1, 19) = 7.406, p < .014.
Personality measures. Participants’ scores for the personality measures were as follows:
(i) for SCS, M = 61.63, SEM = 1.99; (ii) for BAQ, M = 77.32, SEM = 2.88;(iii) for Awareness-
BPI, M = 2.78, SEM = 0.169; (iv) for Autonomic Reaction-BPI, M = 1.52, SEM = 0.061; (v) for
Absorption –MIHT, M = 20.84, SEM = 1.267; (vi) for Worry – MIHT, M = 23.95, SEM = 1.417.
Correlations. Participants’ mean reaction times correlated positively with their
descriptiveness ambivalence scores for interoception, r (19) = -.537, p < .018. No other
correlations between reaction times and other behavioral or personality measures were found.

Functional Imaging Data
Self versus one-back baseline. A conjunction analysis of the higher-level analysis results
for each condition compared with baseline revealed that all four conditions overlapped in terms
of activity in the following regions: bilaterally in the ventromedial prefrontal cortex, posterior

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medial frontal gyrus, inferior PMC (comprising inferior precuneus, and the posterior cingulate
and retrosplenial cortices), cuneus, inferior frontal gyrus/ anterior insula, and cerebellum; and in
the left superior and middle prefrontal gyri, middle and superior temporal gyri, angular gyrus,
lateral occipital gyrus, hippocampus, and amygdala (Figure 3.2).

Figure 3.2. Experimental conditions versus baseline. The images derive from a
conjunction analysis, and show brain regions with significantly greater signal during all of the
self conditions relative to the baseline n-back task.

Core self versus autobiographical self
Core self > autobiographical self (traits and facts). Interoception compared with the
autobiographical-self conditions (traits and facts considered together) yielded greater activity
bilaterally in the most superior and anterior PMC (i.e., comprising a cluster in the superior
precuneus, adjacent to the ascending ramus of the cingulate sulcus), middle and inferior frontal
gyri, inferior part of precentral gyrus, inferior part the postcentral gyrus, supramarginal gyrus;
middle temporal gyrus and adjacent lateral occipital cortex and insula (including anterior and
posterior insula); in the left most superior and posterior part of the PMC (i.e., comprising a

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cluster in the superior precuneus adjacent to the occipitoparietal sulcus), and in the left
extrastriate body area (here, as in the rest of this publication, the location of extrastriate body area
is based on the coordinates published in (Downing, Jiang, Shuman, & Kanwisher, 2001); and in
the right superior and inferior temporal gyri (Table 3.2).

Table 3.2. Activation peaks for the contrast interoception minus autobiographical self (traits and
facts). Coordinates are in the MNI-152 standard space.

Structure H x y z Z
Posteromedial cortex L -14 -72 28 4.17
R 8 -30 44 3.7
Middle frontal gyrus/inferior frontal gyrus L -38 38 16 4.86
R 52 50 6 3.6
Inferior frontal gyrus/ precentral gyrus L -54 -2 10 5.37
R 60 2 8 4.69
Postcentral gyrus/ supramarginal gyrus L -56 -28 32 5.21
R 66 -32 44 4.87
Middle temporal gyrus/ lateral occipital gyrus
(extrastriate body area)

L
-56 -58 4 5.23
64 -50 10 2.39
Superior temporal gyrus R 46 -14 -8 3.25
Inferior temporal gyrus/ temporal pole R 38 -6 -38 3.77
Insula L -34 8 10 5.72
R 36 10 12 5.14

Exteroception compared with autobiographical self conditions (traits and facts considered
together) showed greater activity bilaterally in a posterior part of the anterior cingulate (i.e.,
midcingulate) and adjacent medial prefrontal cortex (i.e., superior frontal gyrus); the most
superior part of the PMC (i.e., in the superior precuneus, extending from its anterior limit to its
posterior limit); orbitofrontal cortex, basal forebrain, superior and middle frontal gyri adjacent to
the precentral sulcus (premotor cortices); the middle and inferior frontal gyrus adjacently to the
inferior frontal sulcus; the most inferior part of the precentral gyrus; supramarginal gyrus,

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superior parietal lobule, and insula (including anterior and posterior insula); in the left inferior
temporal and fusiform gyri, and extrastriate body area (Table 3.3).
A conjunction analysis revealed that, compared with autobiographical self, both
exteroception and interoception yielded greater activity bilaterally in the most superior and
anterior part of the PMC; in the inferior and middle frontal gyri, inferior part of the precentral
gyrus, supramarginal gyri, and insula (including bilaterally the posterior insula, and the right
anterior insula); in the left most superior and posterior part of the PMC, superior parietal lobule,
cuneus, and extrastriate body area (Figure 3.3; Table 3.4).

Table 3.3. Activation peaks for the contrast exteroception minus autobiographical self (traits and
facts). Coordinates are in the MNI-152 standard space.

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Structure H x y z Z
Medial frontal gyrus/ anterior cingulate cortex L -2 20 46 4.12
R 4 22 48 4.05
Precuneus/ superior parietal lobule L -14 -72 44 5.8
Precuneus R 12 -74 42 5.76
Orbitofrontal cortex L -20 38 -18 4.92
R 18 34 -18 4.23
Basal forebrain L -12 14 -14 2.97
R 16 10 -18 3.02
Superior frontal gyrus/ middle frontal gyrus L -24 0 52 4.31
R 30 4 64 4.39
Inferior frontal gyrus/ middle frontal gyrus L -38 42 12 6.45
R 42 42 4 5.3
Inferior frontal gyrus/ precentral gyrus L -54 8 6 4.64
R 56 10 4 4.5
Inferior temporal gyrus/ fusiform gyrus L -44 -52 -14 4.53
Supramarginal gyrus/superior parietal lobule L -62 -24 28 6.06
R 58 -38 40 5.53
Superior parietal lobule L -36 -48 38 6.28
Middle temporal gyrus/ lateral occipital gyrus
(extrastriate body area) L -58 -64 6 4.78
Insula L -40 -14 -4 5.55
R 38 -16 -4 4.95

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Figure 3.3. Interoception and exteroception compared with autobiographical-self conditions. The
images derive from a conjunction analysis for the following contrasts: interoception > (facts +
traits), and exteroception > (facts +traits). Thus these brain regions showed greater signal for
core self-related questions than for autobiographical questions.

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Table 3.4. Activation peaks for a conjunction analysis for exteroception minus autobiographical
self (traits and facts), and for interoception minus autobiographical self. Coordinates are in the
MNI-152 standard space.
Structure

H x y z Z
Posteromedial cortex L -4 -52 58 3.11
R 4 -54 58 3.40
Posteromedial/ cuneus L -8 -76 42 4.12
Inferior frontal gyrus/ middle frontal gyrus L -38 38 16 4.84
R 50 48 8 3.59
Precentral gyrus L -56 10 6 4.27
R 56 10 4 4.39
Supramarginal gyrus L -56 -28 32 4.78
R 56 -24 28 4.64
Middle temporal gyrus/ lateral occipital gyrus
(extrastriate body area)
L
-58 -62 6 4.13
Superior parietal lobule L -32 -52 40 3.96
Insula L -40 -12 -4 5.34
R 40 -4 -8 4.45

Autobiographical self > core self (interoception and exteroception). Facts compared
with core self (interoception and exteroception) yielded greater activity bilaterally in the
orbitofrontal cortex, MPFC, anterior cingulate cortex (ACC), paracentral gysus, inferior PMC
(i.e., the posterior cingulate cortex, retrosplenial cortex, and approximately inferior half of the
precuneus); middle and superior frontal gyri adjacently to the superior frontal sulcus; anterior part
of the inferior frontal gyrus; superior parts of the precentral and postcentral gyri; superior parietal
lobule, angular and lateral occipital gyri, middle temporal gyrus, temporal pole, thalamus,
caudate, putamen, accumbens, hippocampus, and amygdala; in the left anterior insula; and in the
right inferior temporal gyrus (Table 3.5).

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Table 3.5. Activation peaks for facts minus core-self (interoception and exteroception).
Coordinates are in the MNI-152 standard space.

Structure x y z Z
Medial prefrontal cortex/ anterior cingulate cortex L -6 52 -10 6.57
R 2 56 -8 6.31
Paracentral gyrus L -2 -14 54 3.02
R 4 -22 58 2.95
Posteromedial cortex L -4 -58 32 6.52
R 8 -52 22 6.93
Inferior frontal gyrus/ orbitofrontal cortex L -44 34 -14 4.12
R 40 34 -18 4.54
Middle frontal gyrus/ superior frontal gyrus L -38 18 42 5.29
R 26 26 40 5.33
Postcentral gyrus L -46 -22 62 4.07
R 16 -26 54 3.84
Precentral gyrus/ postcentral gyrus L -30 -16 76 3.91
R 16 -32 62 3.4
Superior parietal lobule/ lateral occipital cortex/
angular gyrus L -48 -70 36 6.53
R 42 -56 34 5.64
Middle temporal gyrus/ temporal pole L -58 -10 -20 6.7
Middle temporal gyrus/ inferior temporal gyrus R 60 -6 -16 5.96
Temporal pole R 40 26 -32 5.19
Thalamus L -4 -2 6 3.94
R 2 -10 6 3.72
Caudate/ accumbens L -6 12 -6 5.01
R 6 12 6 4.31
Hippocampus L -24 -18 -16 5.95
R 22 -20 -16 5.29
Amygdala L -14 -6 -16 3.61
R 32 -10 -16 3.93
Insula L -28 -12 -12 3.42

Traits compared with core self (interoception and exteroception) showed greater level of
activity bilaterally in the orbitofrontal cortex, MPFC, ACC, paracentral gyrus, inferior PMC
(comprising the inferior precuneus and the most superior part of the posterior cingulate cortex);
superior parts of the precentral and postcentral gyri; middle temporal gyrus, temporal pole,

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anterior insula, caudate, putamen, accumbens and thalamus; in the left superior parietal lobule
and angular gyrus; and in the right amygdala (Table 3.6).

Table 3.6. Activation peaks for traits minus core-self (interoception and exteroception).
Coordinates are in the MNI-152 standard space.

Structure H x y z Z
Medial prefrontal cortex/ anterior cingulate cortex L -4 30 -6 4.86
R 8 54 16 5.42
Paracentral gyrus L -4 -26 54 3.23
R 4 -32 60 3.9
Posteromedial cortex L -4 -52 26 4.78
R 6 -54 24 4.39
Inferior frontal gyrus/ orbitofrontal cortex L -46 28 2 4.07
R 42 30 -20 4.04
Precentral gyrus L -48 -24 64 4.01
Precentral gyrus/ postcentral gyrus R 44 -18 66 4.16
Postcentral gyrus L -42 -30 68 4.44
Temporal pole L -54 4 -36 4.72
R 34 28 -32 4.03
Middle temporal gyrus L -62 -12 -14 4.82
R 60 -6 -22 4.45
Lateral occipital cortex L -28 -88 14 4.44
R 36 -90 -8 5.33
Superior parietal lobule/ angular gyrus L -54 -64 46 3.61
Insula L -28 12 12 3.35
Insula/ inferior frontal gyrus R 40 14 -14 2.42
Hippocampus L 22 -20 -12 3.53
Caudate/ putamen/ acumbens L -6 14 -4 3.40
R 6 10 -4 3.59
Thalamus L -2 -6 10 3.39
R 2 -8 10 3.63
Amygdala 14 -8 -12 2.88

A conjunction analysis revealed that both facts and traits, compared with core self
(interoception and exteroception), yielded greater activity bilaterally, in the orbitofrontal cortex,

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MPFC, ACC, inferior PMC (comprising the inferior precuneus and the most superior part of the
posterior cingulate cortex), middle temporal gyrus, temporal pole, thalamus, caudate, putamen,
accumbens; superior parts of the left precentral and postcentral gyri; in the left superior parietal
lobule, angular gyrus and anterior insula; and in the right amygdala (Figure 3.4, Table 3.7).

Figure 3.4. Facts and traits compared with core-self conditions. The images derive from a
conjunction analysis for the following contrasts: facts > (interoception + exteroception), and traits
> (interoception + exteroception). Thus these brain regions showed greater signal for
autobiographical questions than for core-self questions.

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Table 3.7. Activation peaks for the conjunction of facts > coreself and traits > coreself.
Coordinates are in the MNI-152 standard space.

Structure

H x y z Z
Medial prefrontal cortex/anterior cingulate cortex
L -4 36 -10 4.83
R 2 32 -10 4.97
Posteromedial cortex L -4 -52 26 4.78
R 10 -52 22 4.46
Inferior frontal gyrus/ orbitofrontal cortex L -46 26 -10 3.17
R 38 34 -12 3.58
Precentral gyrus/ postcentral gyrus L -48 -22 62 3.71
Temporal pole L -52 12 -28 4.02
R 40 24 -36 4.02
Middle temporal gyrus L -62 -12 -14 4.83
R 62 -6 -22 4.43
Lateral occipital cortex L 34 -90 -8 4.06
Superior parietal lobule/ angular gyrus L -50 -66 36 3.51
Insula L -28 12 -12 3.35
Caudate/ putamen/ accumbens L -6 14 -6 3.25
R 4 14 -8 3.78
Thalamus L -2 -6 10 3.39
R 4 -2 6 3.29
Amygdala R 12 -6 14 2.75

Interoception versus exteroception
Interoception, compared with exteroception, yielded greater activity bilaterally in MPFC,
ACC, paracentral gyrus, inferior PMC (comprising the posterior cingulate cortex, and inferior
precuneus), precentral and postcentral gyri, superior and medial temporal gyri, lateral occipital
gyrus, angular gyrus, and insula (clusters bilaterally in the anterior insula, and in the left posterior
insula); in the left supramarginal gyrus, superior parietal lobule, hippocampus, caudate/

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accumbens, and extrastriate body area (Figure 3.4, Table 3.8).

On the other hand, the reverse contrast (exteroception > interoception) yielded greater
activity bilaterally in superior the PMC (comprising the most superior part of the precuneus,
extending from its anterior limit to its posterior limit), frontal pole and orbitofrontal cortex; in the
middle and inferior frontal gyri adjacently to the inferior frontal sulcus; in the superior and
middle frontal gyrus adjacently to the precentral sulcus (premotor cortices); in the supramarginal
gyrus, and superior parietal lobule; in the left inferior frontal gyrus adjacently to the precentral
sulcus (premotor cortex), and extrastriate body area (Figure 3.5, Table 3.8).

Figure 3.5. Interoception versus exteroception. The red-yellow color scale shows brain regions

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with significantly greater signal for interoception than for exteroception. The blue-green scale
shows brain regions with greater signal for exteroception than for interoception.

Table 3.8. Activation peaks for interoception versus exteroception. Coordinates are in the MNI-
152 standard space
Structure H x y z Z

Interoception > exteroception
Medial prefrontal cortex L -4 48 -10 5.4
R 6 60 16 4.84
Anterior cingulate cortex L -2 42 -8 5.2
R 2 40 -8 5.01
Paracentral gyrus L -4 -34 64 2.84
R 10 -34 70 3.01
Posteromedial cortex (posterior cingulate cortex) L -4 -18 40 4.42
R 2 -18 40 4.38
Posteromedial cortex (precuneus) L -2 -48 36 4.5
R 2 -48 32 4.02
Superior frontal gyrus L -18 46 48 3.81
Precentral gyrus/ postcentral gyrus L -36 -24 70 4.39
R 64 4 18 3.91
Superior temporal gyrus/ medial temporal gyrus L -56 -6 -12 5.32
R 62 -4 -10 5.42
Temporal pole L -54 10 -24 4.21
R 50 18 -24 4.95
Lateral occipital gyrus L -40 -84 0 4.28
R 34 -90 18 4.76
Lateral occipital gyrus (extrastriate body area) R 54 -68 6 2.87
Supramarginal gyrus/angular gyrus L -44 -38 22 4.23
R 62 -50 22 4.7
Superior parietal lobule L -50 -68 36 4.23
Hippocampus L -26 -14 -14 3.41
Caudate /accumbens L -12 6 -8 3.78
Insula L -40 8 -8 4.03
R 40 10 -8 3.04

Exteroception > interoception
Posteromedial cortex L -10 -70 52 4.99

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R 4 -68 48 5.09
Frontal pole/ orbitofrontal L 30 46 -16 4.21
R -22 54 -18 2.85
Superior frontal gyrus/ middle frontal gyrus L -26 6 64 4.84
R 30 6 60 5.06
Precentral gyrus/ inferior frontal gyrus/ middle frontal gyrus L -52 6 36 4.55
Supramarginal gyrus/ superior parietal lobule L -62 -26 22 5.17
R 46 -42 60 5.28
Middle temporal gyrus/lateral occipital gyrus (extrastriate body area) L -52 -66 -2 4.17
Facts versus traits. Facts compared with traits revealed greater activity bilaterally in the
MPFC, PMC (comprising all the PMC except for the most superior and anterior part); superior
and middle frontal gyri, including clusters adjacent to the precentral sulcus (premotor cortices);
supramarginal and angular gyri, superior parietal lobule, middle and inferior temporal gyri,
amygdala, hippocampus and hippocampal formation, fusiform gyrus, and cerebellar cortex, and
in the left frontal pole, and pons (Figure 3.6, Table 3.9).
The reverse showed that activity bilaterally in the lateral occipital gyrus, and in the right
MPFC, posterior ACC (midcingulate cortex) and angular gyrus was greater for traits than for
facts (Figure 3.6, Table 3.9).

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Figure 3.6. Facts versus traits. The red-yellow color scale shows brain regions with significantly
greater signal for facts than for traits. The blue-green scale shows brain regions with greater
signal for traits than for facts.
Table 3.9. Activation peaks for facts versus traits. Coordinates are in the MNI-152 standard
space

Structure

H x y z Z

Facts > traits
Medial prefrontal cortex R/L 0 56 -4 5.29
L -6 52 -8 5.14
R 6 46 -10 4.44
Posteromedial cortex L -4 -60 14 6.34
L/R 0 -60 14 6.29
Frontal pole L -16 64 8 3.5
Superior/middle frontal gyri L -22 20 48 5.13
R 26 22 48 5.44
Supramarginal gyrus/angular gyrus/ superior parietal lobule L -46 -68 32 6.33
R 42 -74 38 6.02

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Middle/ inferior temporal gyrus L -58 -48 -8 6.08
R 62 -44 -8 5.69
Amygdala L -22 -6 -12 3.10
R 22 -8 -20 2.82
Hippocampus/ hippocampal formation L -20 -18 -20 4.42
R 24 -20 -16 4.37
Fusiform gyrus L -24 -38 -14 5.32
R 30 -32 -18 4.09
Cerebellar cortex L -12 -74 -28 3.93
R 48 -64 -24 4.03
Pons L -10 -30 -32 3.76

Traits > facts
Lateral occipital gyrus L -34 -94 16 4.39
R 40 -92 -8 3.9
Angular gyrus R 54 -58 2 2.9
Anterior cingulate cortex/ posterior medial frontal gyrus L/R 0 34 24 4.23

Summary of results in relation to cortical midline structures (CMSs). In order to
summarize and to provide an additional way to visualize the level of activity in CMSs across
conditions mean parameter estimates (PE) for each condition-minus-baseline in ROI-masks for
the MPFC and PMC were calculated. The ROIs were determined by activation peaks yielded in
these regions for the contrasts described above (Table 3.10).

Table 3.10. Activation peaks (and the corresponding contrasts) used for ROI masks of CMSs.

Contrast H MNI coordinates Z
x y z

Medial prefrontal cortex/ anterior cingulate cortex

Autobiographical self > core self L -2 54 16 5.23
R 10 52 14 4.38
L -2 58 -6 4.87
R 2 58 -6 4.72
L -4 36 -10 4.83
R 2 32 -10 4.97

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Traits > facts L -2 34 26 3.91
R 2 32 24 3.97

Posteromedial cortex
Core self > autobiographical self L -4 -52 58 3.40
R 4 -54 58 3.13
Autobiographical self > core self L -4 -52 26 4.78
R 10 -52 22 4.46
Exteroception > interoception L -10 -70 52 4.99
R 4 -68 48 5.09
Interoception > exteroception L -4 -12 44 4.43
R 2 -18 40 4.38
L -2 -48 36 4.5
R 2 -48 32 4.02
Facts > traits L -4 -60 14 6.34
R 10 -52 10 5.63
L -6 -38 34 6.24
R 10 -42 34 6.08
L -2 -66 44 5.78
R 2 -68 46 6.03

Medial prefrontal cortex and anterior cingulate cortex. The MPFC (along with adjacent
subgenual and pregenual ACC) yielded greater activity for autobiographical self than for core self
(Figure 3.7). In addition, the MPFC showed greater activity for facts than for traits (Figure 3.7):
and for interoception than for exteroception (Figure 3.7). A posterior and rostral part of the ACC
(the midcingulate cortex) showed, however, greater activity for traits than for any other
conditions (3.7).
Posteromedial cortex. The most superior PMC was more active for exteroception than for
interoception, and for facts than for traits (Figure 3.8). In addition, the most superior and anterior
PMC was more active for exteroception than for interoception (Figure 3.8).
The most inferior PMC, comprising the inferior precuneus, and the posterior cingulate
cortex, was more active: (i) for autobiographical-self conditions than for core-self conditions; (ii)

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for facts than for traits; (iii) for interoception than for exteroception (Figure 3.9).

Figure 3.7. Parameter estimates for each condition in anterior CMSs. ROIs consisted of spheres

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of 5mm radius centered on activation peaks in the anterior CMSs (Table 3.10) from the
conjunction analyses. MNI coordinates (x, y, z) in parentheses; error bars represent SEM.

Figure 3.8. Parameter estimates for each condition in the superior PMC. ROIs consisted of
spheres of 5mm radius centered on activation peaks in the superior PMC (Table 3.10) from the
conjunction analyses. MNI coordinates (x, y, z) in parentheses; error bars represent SEM.

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Figure 3.9. Parameter estimates for each condition in the inferior PMC. ROIs consisted of
spheres of 5mm radius centered on activation peaks in the inferior PMC (Table 3.10) from the

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conjunction analyses. MNI coordinates (x, y, z) in parentheses; error bars represent SEM.
Between-subject factors
Importance. Negative correlations between mean participants’ importance ratings for the
information evaluated and brain activity were found for all the four conditions, as follows (Table
3.11):
(i) for facts, bilaterally in the medial prefrontal cortex;
(ii) for traits, bilaterally in the inferior posteromedial cortex, and in the right thalamus;
(iii) for interoception, bilaterally in the posteromedial cortex, left thalamus and
mesencephalon;
(iv) for exteroception, bilaterally in the posterior medial prefrontal gyrus, paracentral
gyrus, anterior cingulate cortex, posteromedial cortex (two clusters located in the
more posterior part of the posteromedial cortex, one relatively more dorsal, the other
relatively more ventral), middle and superior frontal gyri, superior temporal gyrus and
temporal pole, and insula; and in the left inferior frontal gyrus, precentral gyrus,
middle and inferior temporal gyri, and angular and supramarginal gyri.

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Table 3.11. Brain activity and participants’ importance ratings. Coordinates (x, y, z; MNI-152
standard space and) and Z-scores correspond to the activation peaks (clusters Z > 2.3; cluster
probability p < .05) negatively correlated with participants’ mean importance ratings.
Structure H x y z Z

Autobiographical-self
Facts
Medial prefrontal cortex L -8 60 4 3.51
R 14 54 4 3.38

Traits
Posteromedial cortex L -2 -50 12 2.7
R 4 -46 20 3.36
Thalamus R 8 -24 10 3.71

Core self

Interoception
Posteromedial cortex L/R 0 -46 12 3.77
Thalamus/ mesencephalon L -6 -28 0 3.74

Exteroception
Medial frontal gyrus L -4 -4 50 3.80
R 6 2 46 3.63
Anterior cingulate cortex L -4 28 20 3.53
R 2 14 38 3.02
Paracentral gyrus L -4 -22 58 3.39
4 -26 54 2.99
Posteromedial L/R 0 -60 42 3.18

Middle frontal gyrus/ superior frontal gyrus L -30 4 52 4.27
R 22 8 52 3.51
Inferior frontal gyrus L -48 8 -4 3.57
58 10 20 4.03
Precentral gyrus L -50 6 46 4.09
Superior temporal gyrus/ temporal pole L -52 6 16 2.98
R 58 12 -16 3.44
Middle temporal gyrus/ inferior temporal gyrus L -52 -10 -30 2.89
Angular gyrus L -62 -56 10 2.89
Supramarginal gyrus L -50 -48 34 2.92
Insula L -42 2 -4 2.55
R 42 2 -8 3.64

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Descriptiveness ambivalence. Mean participants’ descriptiveness ambivalence scores
correlated positively with brain activity for traits in the following regions: bilaterally, the anterior
cingulate and medial prefrontal cortex; and right superior frontal gyrus, insula and adjacent
inferior frontal gyrus (Table 3.12). No other negative correlations were found for any of the
remaining conditions.

Table 3.12. Brain activity for traits and participants’ descriptiveness ambivalence
scores. Coordinates (x, y, z; MNI-152 standard space and) and Z-scores correspond to the
activation peaks (clusters Z > 2.3; cluster probability p < .05) positively correlated with
participants’ mean descriptiveness ambivalence scores for traits.
Structure H x y z Z

Anterior cingulate cortex L/R 0 36 -8 4.23
Medial prefrontal cortex R 4 44 32 3.10
Superior frontal gyrus R 14 60 32 3.27
Inferior frontal gyrus R 50 28 -12 4.49
Insula R 34 16 -12 3.61

Mean participants’ descriptiveness ambivalence scores correlated negatively with brain
activity for interoception and for exteroception, as follows (Table 3.13):
(i) for interoception, bilaterally in the anterior cingulate cortex, posterior medial
frontal gyrus, hippocampus and hippocampal formation, paracentral gyrus,
superior and anterior posteromedial cortex (adjacent to the paracentral gyrus), and
fusiform gyrus; right postcentral gyrus, superior parietal lobule, amygdala and

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cerebellum; and left posteromedial cortex, lateral occipital cortex, middle temporal
gyrus, temporal pole, and pons;
(ii) for exteroception, bilaterally in the pons and cerebellum.

Table 3.13. Brain activity for interoception and exteroception, and participants’ descriptiveness
ambivalence scores. Coordinates (x, y, z; MNI-152 standard space and) and Z-scores correspond
to the activation peaks (clusters Z > 2.3; cluster probability p < .05) negatively correlated with
participants’ mean descriptiveness ambivalence scores for interoception and exteroception.

Structure H x y z Z

Interoception

Medial prefrontal cortex/ anterior cingulate cortex L -2 30 -8 3.5
R 2 54 8 3.33
Paracentral gyrus/ posteromedial cortex L -2 -26 56 2.81
R 8 -42 70 3.94
Postcentral gyrus R 22 -30 58 3.82
Superior parietal lobule R 16 -50 62 3.69
Posteromedial cortex/
Lateral occipital cortex
L
-10 -86 46

2.94
Lateral occipital cortex L -40 -78 32 3.46
Middle temporal gyrus L -52 -12 -18 3.77
Temporal pole L -60 6 -20 3.12
Hippocampus/ parahippocampal formation L -22 -16 -14 3.18
R 24 20 -12 3.76
Amygdala R 20 -4 18 3.49
Fusiform gyrus/ cerebellum R 28 -30 -28 3.51
Fusiform gyrus L -30 -34 -18 3.43
Pons L -12 -18 -34 3.62

Exteroception
Pons L -2 -36 -28 3.17
R 12 -32 -40 3.39
Cerebellum L -8 -52 -32 3.48
R 20 -42 -38 3.67

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Memory. Participant’s estimates of the amount of memory elicited by the interoception
questions correlated negatively with brain activity during interoception in the right superior
temporal gyrus (MNI coordinates: 68, -28, 6; Z-score = 3.95), and middle temporal gyrus (MNI
coordinates: 62, -52, -6; Z-score = 3.16).
Participants’ estimates of memory required to answer trait questions correlated negatively
with brain activity bilaterally in the lateral occipital cortex and in the right middle temporal gyrus
(Table 3.14).

Table 3.14. Brain activity and participants’ estimates of amount of memory retrieved to answer
questions for traits. Coordinates (x, y, z; MNI-152 standard space and) and Z-scores correspond
to the activation peaks (clusters Z > 2.3; cluster probability p < .05) negatively correlated with
participants’ estimates of amount of memory retrieved to answer questions for traits.

Self-consciousness scale (SCS). No correlations were observed between participants’
SCS scores and brain activity for conditions (traits, facts, interoception and exteroception), or
contrasts (traits > facts; interoception > exteroception; autobiographical self > core self) of
interest.

Structure H x y z Z

Lateral occipital cortex R 38 -64 42 3.75
L -44 -82 10 4.26
Middle temporal gyrus R 56 -34 6 3.21

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Body-awareness questionnaire (BAQ). Negative correlations between participants’ BAQ
scores and brain activity were found for traits, interoception, and exteroception and for contrasts
traits > facts and exteroception > interoception, as follows: (Table 3.15):
(i) for traits, bilaterally in the anterior cingulate cortex and in the right medial
prefrontal cortex, superior, middle and inferior frontal gyri, and angular gyrus;
(ii) for traits > facts, bilaterally in the anterior cingulate cortex, and in the right
posterior medial frontal gyrus;
(iii) for interoception, in the right inferior and middle frontal gyri;
(iv) for exteroception, bilaterally in the posterior medial frontal gyrus, superior frontal
gyrus, and in the right supramarginal gyrus and superior parietal lobule;
(v) for exteroception > interoception, in the right superior parietal lobule, superior
posteromedial cortex, postcentral gyrus, parietal operculum, planum temporale,
supramarginal gyrus, superior temporal gyrus, and superior parietal lobule.
No correlations were observed between participants’ BAQ scores and brain activity for
facts, or for activity yielded for core self > autobiographical self.

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Table 3.15. Brain activity and participants’ Body-awareness –questionnaire (BAQ)
scores. Coordinates (x, y, z; MNI-152 standard space and) and Z-scores correspond to the
activation peaks (clusters Z > 2.3; cluster probability p < .05) negatively correlated with
participants’ BAQ scores
Structure H x y z Z

Autobiographical-self
Traits
Anterior cingulate cortex L/R 0 32 22 3.10
Medial prefrontal cortex R 6 32 38 3.69
Superior frontal gyrus R 10 8 64 3.87
Middle frontal gyrus/ inferior frontal gyrus R 44 24 18 3.89
Angular gyrus R 64 -48 18 3.66

Traits > facts
Anterior cingulate cortex L -6 42 24 2.89
R 10 44 20 3.21
Posterior medial frontal gyrus R 4 32 36 3.65

Core self
Interoception
Inferior frontal gyrus/
Middle frontal gyrus
R 48 22 24 3.36

Exteroception
Posterior medial frontal gyrus/ superior prefrontal gyrus L -6 -6 68 3.37
R 4 -6 68 3.12

Supramarginal gyrus/ superior parietal lobule R 30 -36 38 4.29

Exteroception > interoception R 24 -50 74 3.42
Superior parietal lobule/precuneus
Postcentral gyrus R 38 -28 60 3.28
Parietal operculum/ planum temporale
Supramarginal gyrus/ superior temporal gyrus

R 46 -30 14 3.87
Superior parietal lobule

R 54 -28 6 2.98

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Awareness - Body Perception Inventory (Awareness – BPI). Participants’ Awareness –
BPI scores scores correlated negatively with activity for traits in the occipital cortex, bilaterally
in the cuneus, and in the right lateral occipital cortex (Table 3.16)

Table. 3.16. Brain activity for traits and participants scores for the Awareness - Body Perception
Inventory (Awareness - BPI). Coordinates (x, y, z; MNI-152 standard space and) and Z-scores
correspond to the activation peaks (clusters Z > 2.3; cluster probability p < .05) for traits
negatively correlated with participants’ Awareness – BPI scores.
Structure H x y z Z

Cuneus L -2 -84 20 2.6
R 2 -82 22 3.06
Lateral occipital cortex R 24 -84 36 3.69

In addition, participants’ Awareness -BPI scores correlated positively with activity
yielded for core self > autobiographical self bilaterally in the cuneus, and in the right parietal
operculum, planum temporale, superior temporal gyrus and angular gyrus (Table 3.17).
No correlations between participants’ Awareness -BPI scores and activity in relation to
other conditions namely (facts, interoception and exteroception), or contrasts (traits > facts;
interoception > exteroception) were found.

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Table 3.17. Brain activity for core self > autobiographical self, and participants Awareness -
BPI. Coordinates (x, y, z; MNI-152 standard space and) and Z-scores correspond to the activation
peaks (clusters Z > 2.3; cluster probability p < .05) for core self > autobiographical self positively
correlated with participants’ Awareness –BPI scores.
Structure H x y z Z
Cuneus L -8 -84 14 3.47
R 16 -98 -6 3.32
Parietal operculum/planum temporale R 36 -32 16 3.39
Superior temporal gyrus R 62 -34 6 2.88
Angular gyrus R 56 -46 12 3.08

Autonomic Reaction - Body Perception Inventory (Autonomic Reaction - BPI).
Participants’ Autonomic –Reaction BPI scores correlated positively with brain activity for facts,
for interoception, exteroception, interoception > exteroception, and core self > autobiographical
self, as follows (Table 3.18):
(i) for facts, bilaterally in the superior frontal gyrus and precentral gyrus; in the right
posterior medial frontal gyrus; and in the left fusiform gyrus and cerebellum;
(ii) for interoception, bilaterally in the posterior medial frontal gyrus; right superior
frontal gyrus, and lateral occipital cortex, and in the left cerebellum;
(iii) for exteroception, in the right superior frontal gyrus, posterior medial frontal
gyrus, inferior frontal gyrus, precentral gyrus, and in the left cerebellum;
(iv) for exteroception > interoception, right paracentral gyrus, and precentral and
postcentral gyri;

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(v) for core self > autobiographical self, bilaterally in the medial prefrontal cortex, in
the left anterior cingulate cortex, and in the right superior temporal sulcus, and
planum temporale.
Table 3.18. Brain activity and participants’ Autonomic Reaction – BPI scores. Coordinates (x, y,
z; MNI-152 standard space and) and Z-scores correspond to the activation peaks (clusters Z >
2.3; cluster probability p < .05) for core self > autobiographical self positively correlated with
participants’ Autonomic –Reaction BPI scores.
Structure H x y z Z

Autobiographical-self
Facts
Superior frontal gyrus/ precentral gyrus L -20 -12 52 3.63
R 34 -10 56 3.37
Superior frontal gyrus/ posterior medial frontal gyrus R 10 6 48 4
Fusiform gyrus/ cerebellum L -32 -46 -24 5.18
Cerebellum L -24 -58 -24 3.98

Core self
Internal
Medial prefrontal gyrus L -2 18 46 2.94
R 4 18 48 3.76
Superior frontal gyrus R 26 16 66 3.95
Lateral occipital cortex R 62 -48 48 4.08
Cerebellum L -30 -48 -26 3.82

Exteroception
Superior frontal gyrus/ posterior medial frontal gyrus R 16 -6 72 3.83
Inferior frontal gyrus R 54 4 18 3.76
Precentral gyrus R 20 -20 64 3.21
Cerebellum L -34 -48 -26 5.21

Exteroception > interoception
Paracentral gyrus R 4 -24 72 3.55
Precentral gyrus/ postcentral gyrus

R 22 -10 76 3.47

Core self > autobiographical self

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In addition, participants’ Autonomic Reaction – BPI scores correlated negatively with
activity yielded for facts, traits and traits > facts, as follows (Table 3.19):
(i) for facts, in the left medial prefrontal cortex, superior frontal gyrus, and frontal
pole;
(ii) for traits, bilaterally in the paracentral gyrus, and in the left superior and anterior
posteromedial cortex;
(iii) for traits > facts, bilaterally in the superior and anterior precuneus, paracentral
gyus, and cuneus.

Table 3.19. Brain activity and participants’ Autonomic Reaction – BPI scores. Coordinates (x, y,
z; MNI-152 standard space and) and Z-scores for activation peaks (clusters Z > 2.3; cluster
probability p < .05) negatively correlated with participants’ Autonomic Reaction – BPI scores.

Medial prefrontal cortex/ anterior cingulate cortex L -6 24 38 3.73
Medial prefrontal cortex R 2 28 42 3.43
Superior temporal sulcus /planum temporale R 64 -28 18 3.99
Superior temporal sulcus R 64 -18 0 2.61
Structure H x y z Z

Facts
Medial prefrontal cortex L -6 48 36 3.35
Superior frontal gyrus/ frontal pole

L
-12 50 34 3.54
Traits
Precuneus/paracentral gryus L -4 -48 62 3.56
Paracentral gyrus R 4 -40 56 3.04

Traits > facts
Precuneus/paracentral gryus L/R 0 -46 62 3.98
Cuneus R 16 -78 0 3.93
L -6 -84 -8 3.32

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Absorption - Multidimensional Inventory of Hypochondriacal traits (Absorption –
MIHT). Participants’ Absorption – MIHT scores correlated positively with activity for
autobiographical-self > core-self in the left middle and inferior frontal gyri, precentral and
postcentral gyri, and superior parietal lobule (Table 3.20). No correlations were found between
participants’ MIHT absorption scores and activity for autobiographical-self or core-self
conditions, nor for activity yielded by contrasts of interest (traits > facts; interoception >
exteroception).

Table 3.20. Brain activity for autobiographical self > core self, and participants Absorption –
MIHT scores. Coordinates (x, y, z; MNI-152 standard space and) and Z-scores correspond to the
activation peaks (clusters Z > 2.3; cluster probability p < .05) for autobiographical self > core self
positively correlated with participants’ Absorption – MIHT scores.
Structure H x y z Z
Middle frontal gyrus/inferior frontal gyrus L -32 34 22 4.06
Precentral gyrus L -34 -22 66 3.31
Postcentral gyrus L -46 -36 58 3.53
Superior parietal lobule L -30 -44 68 3.46

Worry - Multidimensional Inventory of Hypochondriacal traits (Absorption –
MIHT). Participants’ Worry – MIHT scores correlated positively with activity for facts, for
interoception, for interoception > exteroception, and for core self > autobiographical self, as
follows (Table 3.22):
(i) for facts, in the left supramarginal gyrus and superior parietal lobule;

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(ii) for interoception, in the left insula;
(iii) for interoception > exteroception, bilaterally in the cuneus, and fusiform gyrus; in
the right frontal pole, orbitofrontal cortex, middle frontal gyrus, supramarginal and
angular gyri, superior parietal lobule, and lateral occipital cortex; and in the left
lingual gyrus;
(iv) for core self > autobiographical self, bilaterally in the superior posteromedial
cortex, and in the left middle frontal gyrus, postcentral gyrus, insula and putamen.

Table 3.21. Brain activity and participants’ Worry –MIHT. Coordinates (x, y, z; MNI-152
standard space and) and Z-scores correspond to the activation peaks (clusters Z > 2.3; cluster
probability p < .05) positively correlated with participants’ Worry –MIHT scores.

Structure H x y z Z

Autobiographical self
Facts
Supramarginal gyrus/ superior parietal lobule L -64 -42 42 4.76

Core self

Interoception
Insula L -40 -12 20 3.61

Interoception > exteroception

Cuneus L/R 0 -90 4 3.85
Frontal pole R 48 52 4 3.73
Orbitofrontal cortex R 18 50 -18 3.23
Middle frontal gyrus R 42 30 44 3.27
Supramarginal gyrus/superior parietal lobule R 46 -46 36 3.69
Angular gyrus R 46 -52 16 2.72
Lateral occipital cortex R 32 -84 32 3.88
Lingual gyrus/ fusiform gyrus L -26 -64 -10 3.51
R 24 -42 -8 3.46

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Core self > autobiographical self
Superior precuneus L -2 -64 46 4.99
R 2 -64 48 3.93
Middle frontal gyrus L -40 48 20 4.89
Postcentral gyrus L -60 -6 24 3.36
Insula L -36 -12 14 3.89
Putamen L -30 -4 -2 3.48

In addition, participants’ Worry - MIHT scores correlated negatively with activity for
traits in the right anterior cingulate cortex, superior frontal gyrus, posterior medial frontal gyrus,
and precentral and postcentral gyri (Table 3.22).

Table 3. 22. Brain activity for traits and participants’ Worry – MIHT scores. Coordinates (x, y, z;
MNI-152 standard space and) and Z-scores correspond to the activation peaks (clusters Z > 2.3;
cluster probability p < .05) for traits self negatively correlated with participants’ Worry - MIHT
scores.
Structure H x y z Z
Superior frontal gyrus/ posterior medial frontal gyrus R 12 34 60 3.93
Anterior cingulate cortex R 10 34 20 2.82
Superior frontal gyrus/frontal pole R 18 42 54 4.08
Precentral gyrus R 22 -18 74 3.43
Postcentral gyrus R 56 -12 54 3.78

Discussion
The results above reveal a complex picture: some brain regions are preferentially
associated with either core or autobiographical self states; some brain regions are clearly

161
associated with both.
Both core self and autobiographical self questions elicited activity in the midline and
insular cortices, as well as in lateral frontal, temporal and parietal cortices, hippocampus and
amygdala. This anatomical and functional overlap includes regions related to somatosensory and
motor representations (e.g., somatosensory, premotor and motor cortices) and to memory (e.g.,
hippocampus). It thus supports the hypothesis that both autobiographical self and core self states
are, to a certain extent, associated with body-related and memory-related processing.
The data also revealed differences across the conditions. In the sections below, I discuss
those differences relative to activity in regions related to body processes and memory processes,
and to reaction times to self-related questions. In addition, I advance an interpretation for the role
of midline and insular cortices in processing self-related information.

Self-Related Mental States Vary in Terms of the Involvement of Body-Related Brain
Regions
Both core self conditions yielded greater activity in the supramarginal gyrus (SMG) than
autobiographical self conditions. Because the SMG is reciprocally connected with the insular,
somatosensory and premotor cortices (e.g., Andersen et al., 1999), and has been involved in
processing varied body sensations (Committeri et al., 2007) (Kuhtz-Buschbeck et al., 2007; Nour,
Svarer, Kristensen, Paulson, & Law, 2000), this suggests that body-related regions are more
active for core self states than for autobiographical self states. This appears to be further
supported by the comparison between each core self condition with the autobiographical self
conditions. For example, compared with the autobiographical self conditions, interoception was
associated with greater activity in the somatosensory cortices and motor cortices, and

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exteroception, with greater activity in the premotor and motor cortices.
The extrastriate body area (EBA) was more active for core self than for autobiographical
self. Given that the EBA has been shown to be preferentially activated by images of the human
body and body parts (Downing et al., 2001), this finding suggests that, compared with
autobiographical self states, core self states are associated with a greater amount of body-related
visual imagery.
Nonetheless, compared with core self questions, autobiographical self questions elicited a
higher level of activity in varied regions involved in processing emotion-related somatic-
representations, such as the anterior cingulate cortex (Vogt, 2005; Vogt & Palomero-Gallagher,
2013) and the amygdala (Pessoa & Adolphs, 2010). This suggests that autobiographical self
mental states are associated with a greater extent of emotion-related processing, probably having
largely to do with emotional responses to the memories retrieved. Several prior findings are in
line with this view. The subgenual ACC is involved in emotional processes related with memory
retrieval, such as recalling sad memories (reviewed in (Vogt & Palomero-Gallagher, 2013)).
Also, the amygdala has been linked to the consolidation and retrieval of memories with high
emotional content (Dolcos, 2013)
In addition, the posterior and rostral ACC, sometimes designated as midcingulate cortex
(Vogt:2013df), was more active for traits than facts. This difference may relate to decision
processes, given the association between the midcingulate cortex and decision-making
(Ridderinkhof:2004jj; Vogt & Palomero-Gallagher, 2013). Deciding whether a “trait” is self
descriptive is probably less straightforward than deciding whether a “fact” is self descriptive
(Keenan et al., 1992)

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Self-Related Mental States Vary in Terms of the Involvement of Memory-Related Brain
Regions
Memory-related regions were more active for autobiographical self than for core self, as
hypothesized. The anterior temporal cortices, which have been implicated in the retrieval of
semantic knowledge regarding self (Kjaer, Nowak, & Lou, 2002; Lou et al., 2004) and others
(Heide, 2013; Olson, Plotzker, & Ezzyat, 2007), showed greater activity for autobiographical
self conditions than for core self conditions.
In addition, the hippocampus showed greater activity for facts than for traits. Given the
established role of the hippocampus in memory retrieval (see Cohen & Eichenbaum, 1993), this
suggests that mental states evoked by questions about facts elicited greater amount of memory
retrieval than those evoked by questions about traits. This difference may be explained by the
likely possibility that individuals hold a greater number of memory representations for facts than
for traits. Facts are particularly relevant to one’s identity and daily life, and the number of daily
events and experiences related to facts is large. On the other hand, not all traits are relevant to
one’s identity and daily life, and the number of daily events and experiences related to traits in
one’s life is presumably more limited than that related to facts.
The hippocampus also showed greater level of activity for interoception than
exteroception. Along with the participants’ estimates of the amount of memory retrieval elicited,
which were greater for interoception for exteroception, this supports the notion that interoception
are important cues for memory retrieval (Hirsh, 1974), and suggests that interoceptive sensations
trigger greater amount of memory retrieval than exteroceptive sensations.

Self-Related Mental States Depend on Differences across Individuals in Relation to the

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Specific Information Being Processed
These results showed that activity in CMSs for traits and facts correlated negatively with
participants’ importance ratings but correlated positively with participants’ scores for
ambivalence scores and memory estimates. These findings are in line with what was presented
and discussed in the Chapter 2 study.
In addition, for core self conditions, participants’ importance ratings correlated negatively
with activity in CMSs, as well as regions involved in motor and somatosensory processes, such
as the precentral and supramarginal gyri and the insula. These results may indicate that
individuals require lower level of brain activity for body sensations that are important to them
than for those that are less important to them, possibly because individuals tend to process body
sensations that are important to them body sensations more frequently and in less effortful
manner.
Participants’ ambivalence descriptiveness scores correlated negatively with brain activity
generated in the CMSs, lateral temporal and parietal cortices, hippocampus, and amygdala for
interoception. This suggests that body sensations that are not unambiguously present or absent
are associated with lower level of processing in different brain regions, and may well be an
indication that “strength” of a body sensation is commensurate with the level of brain activity in
body-related regions. Moreover, because these correlations involve activity in emotion-related
regions (e.g., amygdala) and memory-related regions (e.g., hippocampus), this may indicate that
a greater level of processing related to emotion and memory occurs for body sensations that are
well defined than for body sensations that are poorly defined.

Self-Related Mental States Depend on Personality Differences across Individuals

165
The results showed that activity generated for autobiographical self conditions depends on
personality measures related to how body sensations tend to be processed.
Similarly to what is observed in Chapter 2 study, participants’ BAQ scores correlated
negatively with activity generated for traits in emotion-related areas (e.g., anterior cingulate
cortex). In addition, participants’ scores BAQ scores correlated negatively with activity generated
for core-self conditions in MPFC and supramarginal gyrus, which suggests that participants who
have a greater tendency to be aware of their body sensations recruit less activity in the relevant
brain regions compared with participants who have a lower tendency in that regard.
Participants’ Autonomous-Reaction scores correlated positively with brain activity
generated for core self conditions in motor and premotor brain regions. In addition, participants’
hypochondria-related scores, Absorption-MIHT, and Worry –MIHT, correlated positively with
activity generated for core self conditions. Altogether, these findings may indicate that those
participants who tend to process body changes in a rather excessive manner recruit greater level
of activity in regions involved in body-related processes for core self conditions than participants
who tend to process body changes in a more moderate manner.
Participants’ difference of activity between core self and autobiographical self correlated
positively with their scores for Awareness –BPI, Autonomous –Reaction BPI, and Worry –
MIHT, which supports the hypothesis that differences of activity between core self and
autobiographical self depend on one’s personality.
Altogether these results confirm the relationship between autobiographical self processes
and one’s personality that was presented in Chapter 2. The data also indicate that the level of
body-related processing for core self mental states depends on personality differences in relation
to how one tends to process body sensations. Specifically, individuals who are more likely to be

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aware of their body sensations seem to require less brain activity during core self states;
nonetheless, individuals who are excessively worried about their body status tend to require
greater level of brain activity during core self states.

Examining One’s Self Varies in Terms of Processing Times
Answering core self questions took longer than answering autobiographical self
questions. This suggests that the representations that are needed to answer core self questions are
less readily available than those accessed to answer autobiographical self questions. To answer
autobiographical self questions, it is necessary to access memory representations for relatively
stable aspects of one’s biography, namely for personality traits and biographical facts. Even
though access to memories of a remote and insignificant life event may be relatively laborious,
access to the memories related to autobiographical self questions was probably relatively
effortless because individuals tend to hold summary representations for the information targeted
by those questions (i.e., facts, and traits) given its relevance to one’s identity and personality
(Klein, 2012).
On the other hand, to answer core self questions, individuals needed to access transitory
maps of one’s ongoing body status. Moreover, the mapping of body changes occurs in different
levels of nervous system, and in part is processed in unconscious manner. Body signals within
the homeostatic range are less readily accessible to consciousness than body signals that deviate
from homeostasis, as shown in heartbeat detection tasks (Khalsa, Rudrauf, Sandesara, Olshansky,
& Tranel, 2009). I note that, in our study, the participants answered “no” to most of the questions

167
targeting negative body sensations for interoception (e.g., hunger) or exteroception (e.g.,
pressure).

Involvement of the MPFC and PMC in Self-Related Mental States
The involvement of default mode network. These data appear to confirm the
involvement of MPFC and PMC, along with other regions of the default mode network (e.g., the
lateral temporal cortex and angular gyrus), in self-related mental states (Qin & Northoff, 2011).
Moreover, the level of activity in those DMN regions was greater for autobiographical self states
than for core self states. This finding supports the notion that DMN regions are particularly
engaged by states in which individuals temporarily disengage from what is happening in the
external world or in their bodies, and focus on the retrieval, display and manipulation of
internally generated representations (e.g., memories and related thoughts).
Intriguingly, the level of activity in the MPFC, inferior PMC, lateral temporal cortex and
angular gyrus, was greater for interoception than for exteroception. This may relate to differences
in memory retrieval between the conditions, but it may well suggest that, compared with
autobiographical self mental states, DMN’s involvement in core self states is more restricted
when the focus is on exteroceptive sensations. Other studies seem to support this suggestion. It
has been shown that DMN activity correlates negatively with activity in the somatosensory
cortices (Fox et al., 2008) and in the auditory and visual cortices (Tian et al., 2007).

The medial prefrontal cortex. As noted above, the level of activity in the MPFC was
greater for: (i) autobiographical self conditions than for core self conditions, (ii) facts than for
traits, (iii) interoception than for exteroception. Because there is substantial evidence that the

168
MPFC assists the participation of emotion-related somatic representations in decision (Bechara,
Tranel, & Damasio, 2000), and evaluative processes (D'Argembeau, 2013), I believe that MPFC
activity during self-related mental states is commensurate with the extent of emotion-related
processing in those states.
The extent of emotion-related processing in a given state is, in turn, probably
commensurate with the number of elements that are being processed and are involved in inducing
an emotional response. In our study, the mental states evoked by the conditions seem to involve
predominantly processing of memories and body sensations. In addition, as noted before,
memories include manifold elements pertaining to the events and experiences from which those
memories derived, while body sensations, particularly within the homeostatic range, are
probably more limited in that regard. Accordingly, memories may have a greater potential of
eliciting emotion-related processing than body sensations, and this may well explain the
difference of activity in the MPFC between core self and autobiographical self. Moreover, it may
also explain the differences of activity in the MPFC between facts and traits because facts are
associated with a greater amount of memory retrieval; likewise for the difference between
interoception and exteroception, given that interoceptive questions seem to elicit greater amount
of memory retrieval.
Findings from other studies support our proposal in relation to the MPFC. The level of
activity in the MPFC has been shown to be commensurate with variables that, in all likelihood,
correlate with the extent of emotional processing, namely: one’s level of experience, familiarity
or affective closeness with the stimuli (i.e., objects or people) that are processed in different
studies. For example, MPFC is more active when individuals process objects with which they
highly experienced than when they process objects with which they are not highly experienced

169
(Lieberman, Jarcho, & Satpute, 2004). In addition, the MPFC’s involvement in processing
information about other people seems to be greater for affectively closer individuals (e.g.,
relatives) than for affectively more distant people (Ochsner et al., 2005; Zhu, Zhang, Fan, & Han,
2007).

The posteromedial cortex and its sub-regions
The superior PMC. The most superior PMC (i.e., superior precuneus) yielded greater
activity for exteroception than for interoception and than for any of the autobiographical self
conditions, suggesting that this region is particularly involved in processing exteroceptive body
changes. Data from other studies support this suggestion. For example, as mentioned before, the
most superior PMC is highly connected with somatosensory cortices and premotor and motor
cortices (Parvizi et al., 2006). It has also been shown that the activity in the superior PMC for
admiration and compassion is greater when those feelings relate to another person’s external
body (e.g., admiration for a person’s performance at gymnastics or compassion for a person’s
physical pain caused by a broken leg) than when the feelings relate to another person’s
“psychological” state (e.g., admiration for a social virtue, such as generosity; and compassion for
someone who grieves the death of a close one) (Immordino-Yang, McColl, Damasio, &
Damasio, 2009).
I note, however, that in our study, the most anterior and superior PMC (i.e., superior
precuneus adjacent to the ascending ramus of the cingulate sulcus) showed greater level of
activity not only for exteroception but also for interoception, compared with the autobiographical
self conditions. This finding suggests that the most anterior and superior PMC is involved in

170
processing varied domains of body sensations, a suggestion that is compatible with findings from
resting state connectivity. Specifically, it has been shown that this region is connected with the
primary and secondary somatosensory cortices as well as with the insular cortices (REF).
The inferior PMC. The most inferior PMC, comprising predominantly the more posterior
PCC, the retrosplenial cortex and the most inferior precuneus, appears to be active during all
conditions. This may indicate that hubs in the PMC are of a relatively general purpose and can
assist varied processes. This indication is supported by findings derived from other studies. For
instance, it is known that the ventral precuneus is a central structure of the so-called default
network (Y. Zhang et al., 2012), and that the retrosplenial cortex is involved in a wide range of
cognitive functions, from memory retrieval, mind wandering, imagination and spatial navigation
tasks (Vann, Aggleton, & Maguire, 2009).
A relatively more dorsal region within the inferior PMC, comprising the inferior
precuneus and adjacent PCC, showed greater activity for autobiographical self than for core self.
It is possible that this activity relates to memory retrieval given the presumable difference of
memory retrieval across the conditions discussed above. In addition, it is known that the inferior
precuneus holds a greater level of connectivity with the hippocampus than the superior precuneus
(S. Zhang & Li, 2012), and the inferior precuneus has been implicated in retrieval of self-related
as well as non-self related memories (Cavanna, 2006).
The most anterior part of the PCC seems to show greater level of activity for
interoception than for exteroception. This is compatible with findings from connectivity studies
showing that the cingulate cortex is anatomically connected with brainstem nuclei related to
interoception (Cameron, 2009).

171
Involvement of the Insular Cortices in Self-Related Mental States
These data seem to confirm that insular cortices are involved in core and autobiographical
self mental states, but their involvement depends on the domain of self that is being processed in
those states. More specifically, the most anterior insular cortex yielded greater activity for the
autobiographical self questions than for core self questions, and the most posterior insular cortex
showed greater activity in the opposite direction. These findings are consistent with a frequent
proposal that the activity in the more posterior insula relates predominantly to processing of
somatic representations regarding “actual” body changes, whereas activity in the more anterior
sectors of the insula are largely involved in processing of somatic representations related to
emotions (reviewed in (Craig, 2002; 2009)). It has also been shown that, in meditators, the
posterior insula shows greater activity for reflecting on one’s body status than for reflecting on
one’s personality traits (Farb et al., 2007).

Conclusion
These data show that examining one’s current body sensations (core self) yields activity
not only in regions specially dedicated to body representations but also to memory. Likewise,
examining historical aspects of oneself (autobiographical self) is associated with activity in
regions related to memory processes well as with activity in regions devoted to somatic
representations, particularly those related to emotion (e.g., anterior cingulate and insular
cortices). The results show that CMSs and insular cortices are involved in core self and
autobiographical self states albeit differently. Furthermore, activity generated for core and
autobiographical self states depends on individual differences in relation to the specific
information being processes and to personality differences regarding how self-related information

172
tends to be processed.

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Chapter 4

Self-related states and brain activity during experimental rest

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Abstract

The investigation of neural basis for self-related processes has focused largely on
brain activity generated for experimental tasks that require individuals to process self-
related stimuli (e.g., questions about themselves), but it may benefit also from
considering brain activity in the absence of an experimental task (i.e., experimental rest).
The meaning of brain activity during experimental rest has not been established,
but it has been proposed that brain activity during rest relates with mental processes
during rest, such as mind wandering (Mason et al., 2007), which raises the possibility that
this activity relates also to self-related states occurring during rest (e.g., thoughts
regarding one’s ongoing body status).
An alternative proposal for the meaning of brain activity during rest defends that
brain activity during rest relates to a default mode of anatomical and functional brain
networks (Raichle et al., 2001). In other words, brain activity during rest is regarded as a
privileged manner to assess the anatomical and functional organization of an individual’s
brain. Moreover, measures of that activity, such as functional intrinsic connectivity
(fcMRI), can be used as correlates of personality, and neurological and psychiatric
disease (Fox & Raichle, 2007). This raises the possibility that fcMRI also relate to
personality differences pertaining to how an individual tends to process self-related
information.
In this study, I addressed the above possibilities by investigating how fcMRI in
DMN regions (Figure 4.1 and Figure 4.2) and in body-related regions (e.g.,
somatosensory and motor cortices, insula and amygdala, Figure 4.3) varies across
individuals in relation to (i) spontaneous thoughts during rest, which were assessed using
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participants’ self-reports and questionnaires measuring one’s tendency to daydream; and
(ii) personality differences in relation to how one tends to process self-related and other-
related information.
The results of this study seem to demonstrate that participants’ fcMRI in DMN
and body-related regions varied with differences in relation to mental processes during
rest as well as to personality. These data should prompt further discussion on self-related
states that are not contingent on a task, and may be relevant to the treatment of
neurological and psychiatric diseases such as depression, anxiety and hypochondria. In
addition, the data should prompt further discussion of the meaning of brain activity
during rest.

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Introduction
The investigation of neural basis for self-related processes has focused largely on
brain activity generated for experimental tasks that require individuals to process self-
related stimuli (e.g., questions about themselves), but it may benefit also from
considering brain activity in the absence of an experimental task (i.e., experimental rest).
There is evidence that certain brain regions, namely medial prefrontal cortex
(MPFC), posteromedial cortex (PMC), lateral parietal and temporal cortices, and
hippocampus are more active during experimental rest or passive tasks (e.g., passive
fixation) than during highly demanding external-oriented tasks (e.g., same-different
discrimination) as reviewed in Buckner et al, 2008.
Although the meaning of brain activity during rest has not been fully elucidated, it
has been suggested that it relates to mental processes that occur during experimental rest
or lapses of attention to the experimental task, such as mind wandering, sometimes called
daydreaming or stimulus-independent thoughts (Smallwood & Schooler, 2006). For
example, it has been shown that activity in the PMC correlates with individuals’
tendencies to daydream or mind wander (Mason et al., 2007). Thus it seem possible that
brain activity during rest could also relate to self states that are not contingent on a task,
including states that occur when individuals are not engaged in any particular task (e.g.,
experimental rest), or those that occur when individuals are engaged in a task but their
minds wander away from that task (i.e., lapses of attention). Nonetheless, this possibility
needs to be tested.
On the other hand, it has also been proposed that brain activity during rest does
not relate specifically to mental processes occurring during rest, but rather a default mode
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of anatomical and functional brain networks that can be recruited for several mental tasks.
Along these lines, the regions indicated above have been designated “Default Mode
Network” (DMN; (Raichle et al., 2001). In addition, measures of DMN activity, such as
functional intrinsic connectivity (fcMRI), which corresponds to correlations of activity
(i.e., coupled intrinsic fluctuations in hemodynamics) (Biswal et al., 1995), have been
regarded as a measure of the functional organization of an individual’s brain and thus a
possible correlate of personality and neurological and psychiatric disease (Fox & Raichle,
2007). Several findings seem to be consistent with this proposal. Differences of fcMRI in
DMN regions have been associated neurological and psychiatric disorders, such
Alzheimer’s Disease (Supekar, Menon, Rubin, Musen, & Greicius, 2008), as well as
certain with personality differences across individuals (Markett et al., 2013; Sheng,
Gheytanchi, & Aziz-Zadeh, 2010; Vaidya & Gordon, 2013). Accordingly, it seems
possible that differences across individuals in relation to one’s tendency to examine and
reflect on self domains may be associated with fcMRI differences in DMN regions, but
this possibility needs to be tested.
In addition to being highly connected with one another, the DMN regions are
connected with other cortical and subcortical regions (Hagmann et al., 2008), which
suggests that the DMN does not operate alone, but may collaborate with other brain
structures. Moreover, it seems likely that such collaboration occurs for processes
underlying self-related mental states.
There is evidence that DMN regions are recruited when individuals retrieve
memories for critical biographic facts (i.e., autobiographical self states). It has been
shown that cortical midline regions, in particular the MPFC and PMC, are engaged when
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individuals reflect on one’s personality traits and biographic facts (reviewed in Araujo et
al., 2013); in addition, the hippocampus supports the retrieval of autobiographical
memories (Conway, 1990). Nonetheless, because memories retrieved in
autobiographical-self states may elicit emotional responses, it is likely that body-related
regions are also recruited during those states. For example, both the amygdala and the
insula have been shown to be active during memory retrieval (Fink et al., 1996). In
addition, body-related regions are also likely to be recruited for self states focusing on
body changes (i.e., core self states). Accordingly, fcMRI in body-related regions needs to
be considered in the investigation of the relationship between brain activity during rest
and self-related processes during rest as well as one’s tendency to examine and reflect on
self domains.
In this study, I addressed the above possibilities by investigating how fcMRI
during rest in DMN regions (Figure 4.1 and Figure 4.2) and body-related regions (e.g.,
somatosensory and motor cortices, insula and amygdala, Figure 4.3) varies across
individuals in relation to (i) spontaneous thoughts during rest, which were assessed using
participants’ self-reports and questionnaires measuring one’s tendency to daydream; and
(ii) personality differences in relation to how one tends to process self-related and other-
related information.
More specifically, the participants were asked to estimate the frequency of
thoughts they had during a rest scan (i.e., passive fixation), for each of the following:
(i) body status, comprising thoughts about interoceptive (e.g., hunger) or
exteroceptive body changes (e.g., feeling pressure on a limb);
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(ii) biographic facts and traits, comprising thoughts about critical aspects of
one’s identity (e.g., one’s occupation) or personality (e.g., kindness);
(iii) past events, comprising thoughts related to previous episodes and
situations (e.g., events happening in the previous month);
(iv) present events, including thoughts about current life situations (e.g., a
problem with a housemate);
(v) future events, comprising thoughts of future situations (e.g., a school exam
the following week).
In addition, participants’ general tendencies to daydream were also assessed using
three scales of the Short Imaginal Processes Inventory (Huba, 1982):
(i) Poor Attention Control Scale (PAC), which measures an individual’s
tendency to daydream (e.g., “No matter how hard I try to concentrate,
thoughts unrelated to my work always creep in.”);
(ii) Guilt and Fear-of-failure Daydreaming (GFFD), which measures an
individual’s tendency to have daydreams with “depressing, frightening,
panicky” qualities (e.g., “My daydreams often contain depressing
events which upset me.”);
(iii) Positive and Constructive Daydreaming (PCDD), which assesses an
individual’s tendency to regard daydreaming in a positive manner (e.g.,
“ A really original idea can sometimes develop from a really fantastic
dream”).
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Two personality measures were used to assesse how participants tend to process
self-related information: the Body Awareness Questionnaire (Shields, Mallory, & Simon,
1989), and Self Consciousness Scale (Fenigstein, Scheier, & Buss, 1975). In addition, I
also used a personality measure that assesses one’s tendency to experience emotional
responses in non-self related stressful situations, Personal Distress (Davis & Association,
1980).
The Self-Consciousness Scale (SCS) (Fenigstein et al., 1975) measures an
individual’s tendency to have conscious thoughts directed to one self. It comprises three
subscales:
(i) Private -SCS, which focuses on thoughts that “deal solely with the self”
(e.g., “I’m always trying to figure myself out” )
(ii) Public – SCS, which focuses on thoughts in relation to oneself in social
situations (e.g., “I’m concerned about the way I present myself”);
(iii) Social Anxiety – SCS, which focuses on the level of anxiety associated
with thoughts related to oneself in social situations (e.g., “I have
trouble working when someone is watching me”).
The Body Awareness Questionnaire (BAQ) measures a person’s tendency to
notice body sensations (e.g., “I notice specific bodily reactions to being overly hungry”),
to predict body-related processes in healthy conditions (e.g., “ I can tell in advance when
I go to bed how well I will sleep that night”), and to predict the onset of certain diseases
(“ I know in advance when I’m getting the flu”) (Shields et al., 1989).
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The Personal Distress Scale, which is part of the Interpersonal Reactivity Index
(Davis & Association, 1980), assesses one’s tendency to experience “discomfort and
anxiety” during emotional situations that do not involve oneself (e.g., “When I see
someone who badly needs help in an emergency, I go to pieces.”).

Figure 4.1. Variables explored in this study. This study explored how brain intrinsic
functional connectivity (fcMRI) varies across individuals in relation to (i) spontaneous
thoughts during rest, which were assessed using participants’ self-reports, and

Spontaneous thoughts
during
rest

Tendency to daydream

Personality

Ongoing
body state
Poor Attention
Control

Body Awareness
Questionnaire

Personality traits
Biographic facts
Positive Constructive
Daydreaming
Private -Self
Consciousness Scale

Past
events
Guilt-Fear of Failure
Daydreaming
Public -Self
Consciousness Scale

Present
events
Anxiety-Self
Consciousness Scale

Future
events
Personal
Distress

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questionnaires measuring one’s tendency to daydream; and (ii) personality differences in
relation to how one tends to process self-related and other-related information.
Participants’ fcMRI during rest were measured for DMN regions, which were
based on the coordinates from previous literature (Andrews-Hanna, Reidler, Sepulcre,
Poulin, & Buckner, 2010) (Table 4.1; Figure 4.2), as well as for anatomical masks of
cortical midline regions (MPFC, ACC, and PMC) and the hippocampus (Figure 4.3),
given the particular interest of these regions in autobiographical self states as indicated
above. In addition, participants’ fcMRI was measured for the following body-related
regions (anatomical masks): the amygdala, and insular, somatosensory and motor cortices
(Figure 4.4).

Table 4.1. DMN regions selected from previous literature (Andrews-Hanna et al., 2010)

Default mode network regions MNI coordinates
ROI x y z
1 Anterior medial prefrontal cortex (aMPFC) -6 -52 -2
2 Dorsal medial prefrontal cortex (dMPFC) 0 52 26
3 Ventral medial prefrontal cortex (vMPFC) 0 26 -18
4 Posterior cingulate cortex (PCC) -8 -56 26
5 Retrosplenial cortex (Rsp) -14 -52 8
6 Temporal pole -50 14 -40
7 Lateral temporal cortex -60 -24 -18
8 Temporal parietal junction -54 -54 28
9 Posterior inferior parietal lobule -44 -74 32
10 Hippocampal formation -22 -40 -12
11 Parahippocampal cortex -28 -20 -26

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Figure 4.2. DMN regions selected from previous literature (Andrews-Hanna et al., 2010)
(8-mm spheres based on the coordinates published in that study).

Figure 4.3. Anatomical masks regions for DMN regions of interest: cortical midline
regions and hippocampal formation.
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Figure 4.4. Anatomical masks for regions involved in somatic processes: insula,
amygdala, precentral gyrus and postcentral gyrus.

I predicted that fcMRI during rest in DMN regions should positively correlate
with:
(i) participants’ reported frequencies of thoughts that do not pertain to one’s
ongoing body status, namely thoughts about facts and traits, and on past,
present and future events;
(ii) participants’ tendencies to daydream (PAC, and PCDD);
(iii) participants’ tendencies to reflect on oneself (Private-, Public-SCS, and
Anxiety –SCS);
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In addition, I predicted that fcMRI during rest in body-related regions should
correlate with:
(i) participants’ reported frequencies of thoughts related to one’s ongoing
body status;
(ii) participants’ tendencies to experience daydream of a negative valence
(e.g., depressing qualities) (GFDD);
(iii) participants’ tendencies to notice body changes (BAQ);
(iv) participants’ tendencies to experience distress during non-self related
emotional situations (PD).

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Methods
Participants
This study included 37 (M = 21.38, SD = 2.38 years old; 18 male and 19 female) of
the 40 participants recruited for the studies described in Chapter 2 and 3, as follows: 17
participants (M = 20.12, SD = 1.32 years old; 8 male and 9 female participants) derived
from Chapter 2 study; and 20 participants (M = 22.5, SD = 2.6 years old; 10 male, 10
female) derived from Chapter 3 study. Two of the 19 participants included in Chapter 2
study did not undergo a resting scan due time constraints. As described previously, all
participants were native English speakers, right-handed, and with no history of
neurological diseases. They were recruited from the University of Southern California
community, and were paid for their participation. They provided written informed
consent following the Institutional and Federal Guidelines.
Procedures
Once inside the scanner, the participants were instructed to keep their eyes open and
to look at the fixation cross. The fixation cross on a grey background was presented using
MATLAB (The Mathworks) coupled with Psychophysics Toolbox Version 3 software
(Brainard 1997). It was projected onto a screen at the end of the scanner bore, which the
participants saw through a mirror mounted on the head coil.
Image Acquisition
All the image acquisition was done with a 3-Tesla Siemens MAGNETON Trio
System. Echo-planar images (EPI) were acquired with the following parameters: TR =
2000 ms, TE = 25 ms, flip angle = 90˚, 64 x 64 matrix, in-plane resolution 3.0 mm x 3.0
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mm, 41 transverse slices, each 3 mm thick, with a field of view covering the whole brain.
The entire run lasted 6 minutes and 6 seconds. The first three volumes acquired served to
allow equilibration of the magnetic field and were therefore deleted.
Structural T1-weighted magnetization-prepared rapid gradient echo (MPRAGE)
images in each subject were also acquired for purposes of registration, with the following
parameters: TR = 1950 ms, TE = 2.3 ms, flip angle = 7˚, 256 x 256 matrix, 193 coronal
slices, 1 mm isotropic resolution.
Questionnaires
After image acquisition, all participants answered the following questionnaires: (1)
Body Awareness Questionnaire (Shields et al., 1989); (2) Private, Public and Anxiety
Self-Consciousness Scales (Fenigstein, Scheier, and Buss, 1975); (3) Poor Attentional
Control, Positive Constructive Daydreaming, and Guilt-Fear of Failure Daydreaming,
parts of the Short Imaginal Process Inventory (Huba, et al., 1982); (4) Personal Distress,
included in the Interpersonal Reactivity Index (David, 1980 and 1983). The participants
also estimated how many thoughts they had during the scan in relation to each of the
following contents: (1) ongoing body status; (2) biographic facts and personality traits;
(3) past events; (4) current events; (5) future events.
Image analysis
All the functional imaging data was preprocessed and analyzed with FSL tools
(FMRIB's Software Library, www.fmrib.ox.ac.uk/fsl).
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Preprocessing. The preprocessing of each participant’s data included the following
steps: head motion correction using MCFLIRT (Jenkinson 2002); slice-timing correction
using Fourier-space time-series phase-shifting; non-brain removal using BET (Smith
2002); spatial smoothing using a Gaussian kernel of FWHM 5 mm; high-pass temporal
filtering (Gaussian-weighted least-squares straight line fitting, with sigma=120.0s).
Registration. Participants’ data were registered to their high-resolution structural
scans (with 7 degree of freedom) and then to standard space (MNI-152 atlas, 12 degrees
of freedom) using FMRIB's Linear Image Registration Tool (FLIRT, Jenkinson 2001,
2002). In addition, FNIRT nonlinear registration (Andersson 2007a, 2007b) was used to
further refine the registration to standard space.
Independent component analysis (ICA). A group-average ICA of resting data was
obtained by analyzing the participants’ resting data with a probabilistic ICA in
MELODIC (Multivariate Exploratory Linear Decomposition into Independent
Components) Version 3.14, part of FSL (FMRIB's Software Library,
www.fmrib.ox.ac.uk/fsl). In brief, the estimation of the components maps required that
the preprocessed data were whitened, projected into a subspace with 20 dimensions, and
decomposed into sets of vectors describing signal variation across (i) the temporal
domain (time-courses), (ii) the subject domain, and (iii) the spatial domain, by using a
fixed-point iteration technique to optimize for non-Gaussian spatial sources distribution
(Hyvarinen, 1999). The estimated component maps were divided by the residual noise
standard deviation, and passed a threshold that resulted from fitting a mixture model to
the histogram of intensity values (Beckmann & Smith, 2004).
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Dual regression. Dual regression was used to analyze the relationship between
resting data and the participants’ measures of personality and estimates (Beckman et al.,
2009; (Filippini et al., 2009). In brief, this analysis included two steps. First, for each
participant, participant-specific time series for each group-level spatial map were
obtained by a regressing the group-average spatial maps (spatial regression) into the
participant’s 4D space-time data. Second, participant-specific spatial maps, one per
group-level spatial map, were obtained by regressing those time series into the
participant’s 4D space-time data. The resulting maps contain, for each participant, one
time point (3D image) per group-level ICA component, and correspond to General Linear
Model (GLM) “parameter estimate” (PE) images.
Correlation analysis. For each participant, we extracted PE values (fcMRI) of the
participant-specific map corresponding, by visually inspection, to the DMN (component
1), for each of regions of interest (ROI)in this study (Figures 4.2, 4.3, and 4.4).
Masks for DMN regions were defined using 8 –mm spheres based on the
coordinates from previous literature (Andrews-Hanna et al., 2010) (Table 4.1; Figure 4.2).
In addition, anatomical masks of cortical midline regions (MPFC, ACC, and PMC) and
the hippocampus (Figure 4.3) , and masks for the amygdala, and insular, somatosensory
and motor cortices were defined using FSL atlas (probability 25% - 100%).

The relationship between fcMRI for each region and the participants’ behavioral and
personality measures (Figure 4.1) were tested by calculating the Pearson Correlation,
using SPSS 18.0.
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The level of statistical significance adopted for the regression analyses was alpha
= .05. All the results presented in the text refer to this level of statistical significance.This
may be considered a lenient statistical threshold particularly considering the possibility of
false positives due to multiple comparisons. On the other hand, more conservative
thresholds may be not advisable because it may increase the frequency of false negatives
given the nature of correlation tests and thus fail to value important relationships.
Nonetheless, for each ROI, I applied a sequential Bonferroni method (Holm, 1979) in
regard to each family of dependent variables: (i) participants’ estimated frequencies of
thoughts during rest; (ii) participants’ tendencies to daydream (PAC, GFDD, and PCDD);
and (iii) participants’ personality measures (BAQ, Private SCS, Public SCS, Anxiety
SCS). The results of this threshold are presented only in Tables 4.10, 4.11 and 4.12.
In addition, when fcMRI of a region was found to correlate with more than one of
above variables, and those variables did not correlate with one another, stepwise linear
multiple regression models were used to test the relationship fcMRI and those parameters
simultaneously, with SPSS 18.0 The level of statistical significance adopted for the
regression analyses was alpha = .05.

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Results
Behavioral data
Estimated frequency of thoughts during rest. Participants’ estimated
frequencies of thoughts about present events (M = 4.46, SEM = .34) were greater than
those of thoughts about any other content evaluated, namely: (i) one’s ongoing body
status (M = 3.27, SEM = .28), F (1, 37) = 6.855, p < .013; (ii) facts and traits (M = 3.2,
SEM = .20), F (1, 37) = 11.210, p < .002; (iii) past events (M = 3.65, SEM = .31), F (1,
37) = 4.037, p < .052; (iv) future events (M = 3.68, SEM = .36), F (1, 37) = 6.257, p
< .017. No other statistically significant differences were observed.
Table. 4.2. Participants’ estimates of the frequency of thoughts during resting scan.

Tendency to daydream. Participants scores related to their tendency to daydream
were as follows (Table 4.3): (i) Poor Attentional Control (PAC), M = 52.14, SEM = 1.21;
(ii) Positive-Constructive Daydreaming (PCDD), M = 39.73, SEM = 1.51; and Guilt-Fear
of Failure Daydreaming (GFDD), M = 43.96, SEM = 1.59.
Thoughts M SEM
Ongoing body status 3.27 0.28
Facts and traits 3.20 0.20
Past events 3.65 0.31
Present events 4.46 0.34
Future events 3.68 0.36
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Personality. Participants’ means scores for the personality measures evaluated
were as follows (Table 4.3): (i) Body Awareness Questionnaire (BAQ), M = 76.41, SEM
= 2.41; (ii) Private - Self Consciousness Scale (SCS), M = 27.00, SEM = 1.09; (iii)
Public-SCS, M = 18.81, SEM = 0.73; (iv) Anxiety-SCS, M = 12.68, SEM = 0.88; (v)
Personal Distress (PD), M = 10.38, SEM = 0.89.
Table 4.3. Participants’ mean and Standard Error Mean (SEM) for the questionnaires
used.
Personality Measures M SEM
Poor Attentional Control 52.14 1.21
Positive-Constructive Daydreaming 39.73 1.51
Guilt-Fear of Failure Daydreaming 43.36 1.59

Body Awareness Questionnaire 76.41 2.41
Private - Self Consciousness Scale 27.00 1.09
Public - Self Consciousness Scale 18.81 0.73
Anxiety - Self Consciousness Scale 12.68 0.88
Personal Distress 10.38 0.89

Gender differences. Male participants were associated with higher Private –SCS
scores (M = 30.4, SEM = 1.34) than female participants (M = 23.79, SEM = 1.36), t (35)
= -3.462, p < .001. Likewise, male participants were associated with higher PCDD scores
for PCDD (M = 55.22, SEM = 1.28) than female participants (M = 49.21, SEM = 1.36), t
(35) = -2.685, p < .011. On the other hand, female participants showed greater PD scores
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197
(M = 12.32 SEM = 1.07) than male participants (M = 8.33, SEM = 1.30), t (35) = 2.377, p
< .023.
Correlations
Thoughts about ongoing body status. Participants’ estimated frequencies of
thoughts about their ongoing body status correlated positively with those of thoughts
about their personality traits and biographic facts, r (37) = .392, p < .017 (Table 4.4); and
with participants’ scores for PD, r(37) = .298, p < .089, but this trend did no reach the
adopted level of statistical significance (Table 4.5).
In addition, participants’ estimated frequencies of thoughts about their ongoing
body status correlated negatively with their GFDD scores, r(37) = - .368, p < .025. (Table
4.5)
Thoughts about personality traits and biographical facts. Participants’ estimated
frequencies of thoughts about their personality traits and biographic facts correlated
positively with those of thoughts about their ongoing body status, r (37) = .392, p < .017,
past events, r (37) = . 390, p < .017, and future events, r (37) = . 371, p < .024 (Table
4.4); and with participants Public-SCS scores, r(37) = .364, p < .027 (Table 4.5).
Thoughts about past events. Participants’ estimated frequencies of thoughts about
past events correlated positively with those of thoughts about their personality traits and
biographic facts, r (37) = . 390, p < .017, present events, r (37) = . 428, p < .008, and
future events, r (37) = . 444, p < .006 (Table 4.4. They also correlated positively with
participants’ Anxiety-Scores, r(37) = .29, p < .082, but this trend did no reach the
adopted level of statistical significance (Table 4.5).
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Thoughts about present events. Participants’ estimated frequencies of thoughts
about present events correlated positively with those of thoughts about past, r (37) = .444,
p < .006, and future events, r (37) = .598, p < .0001 (Table 4.4); and with participants’
scores for Anxiety-SCS, r (37) = .363, p < .027, and PD, r (37) = .402, p < .014 (Table
4.5). They also correlated negatively with participants’ BAQ scores, r(37) = -.393, p
< .016 (Table 4.5).
Thoughts about future events. Participants’ estimated frequencies of thoughts
about future events correlated positively with those of thoughts about their personality
traits and biographic facts, r (37) = . 371, p < .024, past events, r (37) = . 444, p < .006,
and present events, r (38) = .598, p < .0001 (Table 4.4); and with participants’ PD scores,
r(37) = .412, p < .011 (Table 4.5).
Table 4.4. Correlations between participants’ estimated frequencies of thoughts during
rest. Only correlations with significance level p < .10 presented; remaining correlations
marked with “n.s.” Statistically significant correlations (p < .05) marked with “*”.
Body
status
Traits
facts
Past
events
Present
events
Future
events
Body status r(37) .392* n.s. n.s. n.s.
p .017

Traits and facts r(37) .392* .390* 0.309 .371*
p .017 .017 .062 .024

Past events r(37) n.s. .390* .428* .444*
p .017 .008 .006

Present events r(37) n.s. 0.309 .428* .598*
p .062 .008 < .0001
Future events r(37) n.s. .371* .444* .598*
p .024 .006 < .0001
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Table 4.5. Correlations between participants’ estimated frequencies of thoughts, and
scores for questionnaires. Only correlations with significance level p < .10 presented;
remaining correlations marked with “n.s.” Statistically significant correlations (p < .05)
marked with “*”.
PA
C
PCD
D
GFD
D
BAQ Privat
e
SCS
Publi
c
SCS
Anxiet
y
SCS
PD
Body
status
r(37
)
n.s. n.s. -.368* n.s. n.s. n.s. n.s. .298
p .025 .074

Traits
and Facts
r(37
)
n.s. n.s. n.s. n.s. n.s. .364* n.s. n.s.
p .027

Past
events
r(37
)
n.s. n.s. n.s. n.s. n.s. n.s. .29
p .082

Present
events
r(37
)
n.s. n.s. n.s. -
.393*
n.s. n.s. .363* .402
*
p .016 .027 .014

Future
events
r(37
)
n.s. n.s. n.s. n.s. n.s. n.s. n.s. .412
*
p .011

Poor Attentional Control (PAC). Participants’ PAC scores correlated negatively
with their scores for GFDD, r (37) = -.283, p < .090, and BAQ, r (37) = -.272, p < .103,
but these trends did not reach the level of statistical significance adopted (Table 4.6).
Positive Constructive Daydreaming (PCDD). Participants’ PCDD scores
correlated positively with their scores for BAQ, r (37) =.464, p <.004, Private-SCS, r
(37) =.464, p <.004, and Anxiety-SCS, but the last trend did not reach the level of
statistical significance adopted, r (37) = .304, p < .067 (Table 4.6).
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Guilt-Fear of Failure Daydreaming (GFDD). Participants’ GFDD scores
correlated positively with their scores for Private SCS, r (37) =.289, p <.082 and Public
SCS, r (37) = .315, p < .058, but these trends did not reach the level of statistical
significance adopted (Table 4.6).
In addition, participants’ GFDD scores correlated negatively with their estimated
frequencies of thoughts about their ongoing body status, r(37) = - .368, p < .025 (Table
4.5).
Body Awareness Questionnaire (BAQ). Participants’ BAQ scores correlated
positively with their PCDD scores, r (37) = .399, p < .014 (Table 4.5).
In addition, participants’ BAQ scores correlated negatively with their estimated
frequencies of thoughts about present events, r(37) = -.393, p < .016 (Table 4.5), and
Anxiety- SCS scores, r (37) = -.392, p < .016 (Table 4.6).
Private - Self Consciousness Scale (Private –SCS). Participants’ Private-SCS
scores correlated positively with their scores for Public-SCS, r (37) = .663, p < .0001,
PCDD, r (37) =.464, p <.004, and GFDD, but the last trend did not reach the level of
statistical significance adopted, r (37) =.289, p <.082 (Table 4.6).
Public - Self Consciousness Scale (Public – SCS). Participants’ Public- SCS
scores correlated positively with their estimated frequencies of thoughts about their
personality traits and biographic facts, r(37) = .364, p < .027 (Table 4.5), and scores for
Private-SCS, r (37) = .663, p < .0001 and for Anxiety-SCS, r (37) = .367, p < .025. They
also correlated positively with their scores for GFFD, r (37) = .315, p < .058, and PD, r
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(37) = .323, p < .051, but these trends did not reach the level of statistical significance
adopted (Table 4.6).
Anxiety - Self Consciousness Scale (Anxiety –SCS). Participants’ Anxiety -SCS
scores correlated positively with their estimated frequencies of thoughts about past events,
r(37) = .29, p < .082 (Table 4.5); and also with their scores for PCDD, r (37) = .304, p
< .067, and PD, r (37) = .317, p < .056, but these two trends did not reach the level of
statistical significance adopted (Table 4.6).
In addition, participants’ Anxiety -SCS scores correlated negatively with their
scores for BAQ, r (37) = -.392, p < .016, and Public –SCS, r (37) = .367, p < .025.
Personal Distress (PD). Participants’ PD scores correlated positively with their
estimated frequencies of thoughts about present events, r(37) = .402, p < .014 (Table
4.5); and also their scores for Public –SCS , r (37) = .323, p < .051 and Anxiety-SCS, r
(37) = .317, p < .056, but these two trends did not reach the level of statistical
significance adopted (Table 4.5).

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Table 4.6. Correlations between participants’ scores for the questionnaires used. Only
correlations with level of statistical significance p < .10 are presented; remaining
correlations marked with “n.s.” Statistically significant correlations marked with “*”.

BAQ
Private
SCS
Public
SCS
Anxiety
SCS PAC PCDD GFDD PD
BAQ r (37) n.s. n.s. -.392
*
-.272 .399
*
n.s. n.s.
p .016 .103 .014

Private
SCS
r (37) n.s. .663
*
n.s. n.s. .464
**
.289 n.s.
p <.0001 .004 .082

Public
SCS
r (37) n.s. .663
*
.367
*
n.s. n.s. .315 .323
p <.0001 .025 .058 .051

Anxiety
SCS
r (37) -.392
*
n.s. .367
*
n.s. -.304 n.s. .317
p .016 .025 .067 .056

PAC r (37) -.272 n.s. n.s. .186 n.s. -.283 n.s.
p .103 .271 .090

PCDD r (37) .399
*
.464
*
n.s. -.304 n.s. n.s. n.s.
p .014 .004 .067

GFDD r (37) n.s. .289 .315 n.s. -.283 n.s. n.s.
p .082 .058 .090

PD r(37) n.s. n.s. .323 .317 n.s. n.s. n.s.
p .051 .056

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Imaging Data
Identification of DMN map. The group average DMN map included bilaterally
the medial prefrontal cortex (MPFC), anterior cingulate cortex (ACC), posteromedial
cortex (PMC), and lateral temporal (mainly the medial temporal gyrus) and lateral
parietal cortices (mainly the angular gyrus and superior parietal lobule), and the
hippocampus and hippocampus and hippocampal formation (Figure 4.5).

Figure 4.5. Default-mode network, determined by a probabilistic ICA (N = 37
participants).

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Participants’ estimated frequencies of thoughts about their ongoing body
status
DMN regions. Participants’ estimated frequencies of thoughts about their ongoing
body status correlated negatively with fcMRI in the retrosplenial (ROI # 5, Table 4.1),
r(37) = -.350, p < .033 (Figure 4.6); and also with fcMRI in the right posterior
hippocampal formation, r(37) = -.289, p < .083, in the posterior cingulate cortex (ROI # 4,
Table 4.1), r(37) = -.387, p < .086, but these two trends did not reach the adopted level of
statistical significance.
Figure 4.6. Participants’ fcMRI in the left retrosplenial cortex (ROI # 5, Table 4.1)
negatively correlated with their estimated frequencies of thoughts about their ongoing
body status during rest.
Body-related regions. No statistically significant relationship between
participants’ estimated frequencies of thoughts about their ongoing body status and
fcMRI in body-related regions were found.
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Participants’ estimated frequencies of thoughts about their personality traits
and biographical facts
DMN regions. Participants’ estimated frequencies of thoughts about their
personality traits and biographic facts correlated negatively with fcMRI in the posterior
cingulate cortex (ROI # 4, Table 4.1), r(37) = -.342, p < .038 (Figure 4.7).
Figure 4.7. Participants’ fcMRI in the left posterior cingulate cortex (ROI # 4, Table 4.1),
correlated negatively with their estimated frequencies of thoughts about their personality
traits and biographic facts during rest.
Body-related regions. No statistically significant relationship between
participants’ estimated frequencies of thoughts about their personality traits and
biographical facts and fcMRI in body-related regions were found.

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Participants’ estimated frequencies of thoughts about past events
DMN regions. Participants’ estimated frequencies of thoughts about past events
correlated negatively with fcMRI in the temporo-parietal junction (ROI # 8, Table 4.1), r
(37) = -.351, p < .033, and retrosplenial cortex (ROI # 5, Table 4.1), r (37) = -.332, p
< .045 (Figure 4.8); and also with the right posterior hippocampal formation, r(37) = -
.285, p < .088, but this trend did not reach the adopted level of statistical significance.
Body-related regions. Participants’ estimated frequencies of thoughts about past
events correlated negatively with fcMRI in right postcentral gyrus, r (37) = -.323, p
< .051, but this trend did not reach the adopted level of statistical significance.
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Figure 4.8. Participants’ fcMRI in the left retrosplenial cortex (ROI # 5, Table 4.1), and
temporo-parietal junction (ROI # 8, Table 4.1) correlated negatively with their estimated
frequencies of thoughts about past events during rest.

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Participants’ estimated frequencies of thoughts about present events
DMN regions. Participants’ estimated frequencies of thoughts about present
events correlated negatively with fcMRI in right parahippocampal formation, (anterior
and posterior considered together: r [37] = -.393, p < .016; anterior, r [37] = -.387, p
< .018), and in the left parahippocampal formation (anterior and posterior considered
together: r [37] = -.359, p < .029; posterior: r [37] = -.349, p < .034) (Figure 4.9). In
addition, they correlated negatively with fcMRI in the precuneus, but this trend did not
reach the adopted level of statistical significance, r (37) = -.293, p < .078.
Body-related regions. Participants’ estimated frequencies of thoughts about
present events correlated negatively with fcMRI in the right precentral gyrus, r (37) = -
.393, p < .016, and postecentral gyrus, r (37) = -.458, p < .004, and in the left amygdala, r
(37) = .-387, p < .018 (Figure 4.10).

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Figure 4.9. Participants’ fcMRI in the left and right hippocampal formation correlated
negatively with their estimated frequencies of thoughts about present events during rest.

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Figure 4.10. Participants’ fcMRI in the right precentral and postcentral gyri, and left
amygdala correlated negatively with their estimated frequencies of thoughts about present
events during rest.
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Participants’ estimated frequencies of thoughts about future events
DMN regions. Participants’ estimated frequencies of thoughts about future events
correlated positively with fcMRI in the ventromedial prefrontal cortex (ROI # 3, Table
4.1), r (37) =.427, p < .008 (Figure 4.11).
In addition, participants’ estimated frequencies of thoughts about future events
correlated negatively with fcMRI in the right hippocampus (anterior: r[37] = -.416, p
< .010; posterior: r[37] = -.417, p < .010) (Figure 4.12); and in the left hippocampus
(posterior: r[37] = -.337, p < .041), and temporal pole (ROI # 6, Table 4.1), r (37) = -
.368, p < .025.

Figure 4.11. Participants’ fcMRI in vMPFC correlated positively with their estimated
frequencies of thoughts about future events during rest.
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Figure 4.12. Participants’ fcMRI in left and left anterior hippocampal formations, and
left temporal pole correlated negatively with their estimated frequencies of thoughts
about future events during rest.
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Body-related regions. Participants’ estimated frequencies of thoughts about future
events correlated negatively with fcMRI in the right postcentral gyrus, r (37) = -.348, p
< .035 (Figure 4.13); and in the left postcentral gyrus, but this trend did not reach the
adopted level of statistical significance, r (37) = -.298, p < .073.

Figure 4.13. Participants’ fcMRI in right postcentral gyrus correlated negatively with
their estimated frequencies of thoughts about future events during rest.

Poor attentional control (PAC)
DMN regions. Participants’ PAC scores correlated negatively with fcMRI in the
dorsal MPFC (ROI # 2, Table 4.1), r(37) = -.367, p < .026 (Figure 4.14).

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Figure 4.14. Participants’ fcMRI in the dorsal medial prefrontal correlated negatively
with their PAC scores.
Body-related regions. Participants’ PAC scores correlated negatively with
connectivity in the left insula, r(37) = -.428, p < .008 (Figure 4.15).
Figure 4.15. Participants’ fcMRI in the left insula correlated negatively with their PAC
scores.

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Positive constructive daydreaming (PCDD)
DMN regions. Participants’ PCDD scores correlated positively with fcMRI in the
ventral MPFC (ROI #3, Table 4.1), r(37) = .304, p < .068, and negatively with fcMRI in
the temporal parietal junction (ROI # 8, Table 4.1), but these trends did not reach the
level of significance adopted.
Body-related regions. No statistically significant correlations between
participants’ PCDD scores and fcMRI in body-related regions were observed.

Guilt-fear of failure daydreaming (GFDD)
DMN regions. Participants’ GFDD scores correlated positively with fcMRI in the
temporal parietal junction (ROI # 8, Table 4.1), r(37) = .339, p < .040 (Figure 4.16).
Figure 4.16. Participants’ fcMRI in the left temporal parietal junction correlated
positively with their GFDD scores.
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Body-related regions. Participants’ GFDD scores correlated positively fcMRI in
the left precentral gyrus, r(37) = .388, p < .018 (Figure 4.17); and also in the left
amygdala, r(37) = .286, p < .086, and the right amygdala, r(37) = .323, p < .051, but
these trends did not reach the adopted level of statistical significance.

Figure 4.17. Participants’ fcMRI in the left precentral gyrus correlated positively with
their GFDD scores.

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Body awareness (BAQ)
DMN regions. Participants’ BAQ scores correlated positively with fcMRI in the
ventral MPFC (ROI # 3, Table 4.1), but this trend did not reach the adopted level of
statistical significance, r(37) = .295, p < .076.
Body-related regions. Participants’ BAQ scores correlated positively with fcMRI
in the left insula, r(37) = .405, p < .013, amygdala, r(37) = .342, p < .038, and precentral
gyrus, r(37) = .452, p < .005 (Figure 4.18).

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Figure 4.18. Participants’ fcMRI in the left precentral gyrus, insula and amygdala
correlated positively with their BAQ scores.

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219
Private - Self Consciousness (Private -SCS)
DMN regions. Participants’ Private-SCS scores correlated negatively with fcMRI
in the left PCC/ inferior PMC (ROI # 4, Table 4.1), r(37) = -.385, p < .019 (Figure 4.19);
and also bilaterally in the PCC (anatomical mask, Figure 4.2), but this trend did not reach
the adopted level of statistical significance, r(37) = -.302, p < .069.
Figure 4.19. Participants’ fcMRI in the left PCC/ inferior PMC (ROI # 4, Table 4.1)
correlated negatively with their Private SCS scores.
Body-related regions. Participants’ Private-SCS scores correlated negatively with
fcMRI in the right insula, r(37) = -.347, p < .035 (Figure 4.20); and also in the left
postcentral gyrus, but this trend did not reach the adopted level of statistical significance,
r(37) = -.295, p < .076.
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220
Figure 4.20. Participants’ fcMRI in the right insula correlated negatively with their
Private SCS scores.

Public - Self Consciousness (Public -SCS)
DMN regions. Participants’ Public-SCS scores correlated negatively with fcMRI
in the left PCC/ inferior PMC (ROI # 4, Table 4.1), r(37) = -.408, p < .012 (Figure 4.21);
and also in the right parahippocampal formation, but this trend did not reach the adopted
level of statistical significance, r(37) = -.286, p < .087.

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Figure 4.21. Participants’ fcMRI in the left PCC /inferior PMC (ROI # 4, Table 4.1)
correlated negatively with their Public SCS scores.
Body-related regions. No statistically significant relationship between
participants’ Public-SCS scores and intrinsic connectivity of body-related regions were
found.

Anxiety - Self Consciousness (Anxiety -SCS)
DMN regions. Participants’ Anxiety-SCS scores correlated negatively with fcMRI
in the precuneus, r(37) = -.404, p < .013, and in the left PCC/inferior PMC (ROI # 4,
Table 4.1), r[37] = -.520, p < .001 (Figure 4.22). They also correlated negatively with
fcMRI bilaterally in the PCC (anatomical mask), r(37) = -.271, p < .105, and cortical
midline regions (the PMC, ACC and MPFC considered together, Figure 4.3), r(37) = -
.285, p < .087, but these trends did not reach statistical significance.
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Figure 4.22. Participants’ fcMRI in the left PCC and precuneus correlated negatively
with their Anxiety SCS scores.

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223
Body-related regions. Participants’ Anxiety -SCS scores correlated negatively
with fcMRI in the right postcentral gyrus, r(37) = -.328, p < .048 (Figure 4.23); and also
with fcMRI in the right precentral gyrus, r(37) = -.308, p < .064, and in the left
postcentral gyrus, r(37) = -.313, p < .059, and amygdala, r(37) = -.321, p < .053, but
these trends did not reach statistical significance.
Figure 4.23. Participants’ fcMRI in the right postcentral gyrus correlated negatively with
their SCS scores.

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Personal distress (PD)
DMN regions. Participants’ PD scores correlated positively with fcMRI in the
ventral MPFC (ROI # 3, Table 4.1), r(37) = .389, p < .017 (Figure 4.24).
Figure 4.24. Participants’ fcMRI in the ventromedial prefrontal cortex (ROI # 3, Table
4.1) correlated positively with their PD scores.
Body-related regions. Participants’ PD scores correlated negatively with fcMRI
in the right precentral gyrus, r(37) = -.322, p < .052, and in the left amygdala, r(37) = -
.274, p < .101, but these trends did not reach the adopted level of statistical significance.
Summary of correlations. A summary of the correlations between participants’
fcMRI and the variables explored showing a level of significance p = .10 are presented in
Tables 4.7 and 4.8. In addition, tables 4.9, 4.10, and 4.11 present the level of significance
obtained for the correlations between participants’ fcMRI and behavioral measures after
correcting it for multiple corrections, using modified Bonferroni correction for each
family of comparisons in each ROI.
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Table 4.7. Summary of the correlations in the DMN regions . Only correlations with p <.
10 are presented. Statistically significant correlations marked with “*”

H
Positive
Correlations

Negative
Correlations

Dorsal MPFC L/R PAC*

Ventral
MPFC
L/R Thoughts about future
events*
BAQ
PCDD
PD*

PCC/ inferior
PMC
L Thoughts about ongoing
body status
Thoughts about traits and
facts *
Private -SCC *
Public –SCC*
Anxiety –SCC*

Precuneus L/R Thoughts about present
events
Anxiety –SCC*

Retrosplenium L Thoughts about ongoing
body status*
Thoughts about past
events *

Temporal
parietal
junction
L PCDD* Thoughts about past
events *
PCDD

Hippocampal
formation
R Thoughts about ongoing
body status
Thoughts about past
events
Thoughts about present
events*
Thoughts about future
events*
Temporal pole L Thoughts about future
events*
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Table 4.8. Summary of the correlations in the body-related regions. Only correlations
with p < .10 are presented. Statistically significant correlations marked with “*”

H

Positive
Correlations

Negative
Correlations

Insula L BAQ* PAC*

R Private -SCC*

Amygdala L BAQ*
GFDD

Thoughts about present
events*
Anxiety –SCC*
PD

R

Precentral
gyrus
L BAQ*
R PCDD

Thoughts about present
events*
Anxiety –SCC
PD

Postcentral
gyrus
L Thoughts about future
events
Anxiety –SCC
Private -SCS

R Thoughts about past
events*
Thoughts about present
events*
Thoughts about future
events*
Anxiety –SCC*

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Table 4.9. Significance values for correlations between participants’ estimated
frequencies of thoughts during rest corrected using sequential Bonferroni correction
(Holms, 1979). Values of statistical significance lower than .05 marked in bold.

fcMRI

H
Estimated frequencies of thoughts about
Body
status
Traits and
facts
Past
events
Present
events
Future
Dorsal MPFC L/R 1.04 0.91 1.07 1.07 0.67
Ventral MPFC L/R 1.16 1.16 0.36 0.45 0.04
PCC L 0.34 0.19 0.56 0.56 0.54
Precuneus L/R 2.12 1.85 2.12 0.39 1.85
Retrosplenium L 0.13 0.10 0.13 0.36 0.40
Temporal
parietal junction
L 1.43 1.43 0.17 1.43 1.25
Temporal pole L 0.66 0.31 0.66 0.06 0.01
Hippocampus R 1.54 1.54 1.36 0.78 0.12
Insula L 1.40 0.71 1.40 1.59 1.59
R 1.58 1.80 1.80 1.23 1.58
Amygdala L 1.57 1.89 1.89 0.01 0.59
Precentral
gyrus
L 0.86 1.79 1.63 1.28 1.79
R 0.97 0.96 0.79 0.10 0.97
Postcentral gyrus R 0.92 0.59 0.15 0.02 0.14
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Table 4.10. Significance values for correlations found between participants’ tendency to
daydream corrected using sequential Bonferroni correction (Holms, 1979). Values of
statistical significance lower than .05 marked in bold.
fcMRI H PAC PCDD GDFF
Dorsal MPFC L/R 0.08 0.24 0.24
Ventral MPFC L/R 1.32 0.20 1.32
PCC L 1.71 1.71 1.70
Precuneus L/R 1.32 1.13 1.32
Retrosplenium L 1.66 1.66 0.51
Temporal parietal junction L 0.27 0.12 0.12
Temporal pole L 0.89 0.94 0.94
Hippocampus R 1.59 0.51 1.59
Insula L 0.02 0.86 0.73
R 1.06 1.06 0.89
Amygdala L 0.40 0.40 0.26
Precentral
gyrus
L 0.25 0.36 0.05
R 0.52 0.17 0.63
Postcentral gyrus R 2.12 1.85 2.12

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Table 4.11. Significance values for correlations found between participants’ personality
scores corrected using sequential Bonferroni correction (Holms, 1979). Values of
statistical significance lower than .05 marked in bold.
fcMRI H BAQ Private
SCS
Public
SCS
Anxiety
SCS
PD
Dorsal MPFC L/R 2.71 1.75 2.23 2.96 2.96
Ventral MPFC L/R 0.30 1.02 1.02 0.71 0.09
PCC/ inferior PMC L 0.39 0.06 0.05 0.00 0.39
Precuneus L/R 1.45 1.48 1.48 0.07 1.15
Retrosplenium L 2.00 2.05 2.08 2.08 1.42
Temporal parietal junction L 1.73 1.63 1.35 1.73 1.63
Temporal pole L 0.78 1.01 0.43 1.01 0.56
Hippocampus R 1.12 1.37 1.01 1.37 1.32
Insula L 0.06 1.02 1.47 1.69 1.69
R 0.95 0.18 0.48 1.32 1.32
Amygdala L 0.19 0.68 0.68 0.21 0.30
Precentral
gyrus
L 0.02 1.68 1.68 1.29 1.43
R 0.39 0.87 0.67 0.26 0.26
Postcentral gyrus R 1.23 1.23 0.93 0.24 0.93

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Multiple regression
Ventral MPFC. Participants’ fcMRI in the ventral MPFC correlated with their
estimated frequencies of thoughts about future events, and scores for PCDD, BAQ, and
PD. Two stepwise multiple linear regression analyses were performed in order to avoid
collinearity between the independent variables.
A stepwise multiple linear regression of fcMRI in the ventral MPFC on
participants’ estimated frequencies of thoughts about future events, and BAQ and PD
scores rendered two models (Table 4.12): Model 1, including only participants’ estimated
frequencies of thoughts about future events (R
2
= .182); Model 2, including participants’
estimated frequencies of thoughts about future events and BAQ scores (ΔR
2
= .109, p
< .029).
Table 4.12. Models rendered by stepwise multiple regression of fcMRI in the ventral
MPFC on participants’ estimated frequencies of thoughts about future events (“ thought
on future” for short), and BAQ and PD scores.
Model B Std. Error Beta t p
1 Constant .579 2.169 .267 .791
Thoughts
about
future

1.425 .510 .427 2.793 .008
2 Constant -12.170 5.941

-2.049 .048
Thoughts
about
future
1.513 .484 .453 3.128 .004
BAQ .163 .071 .331 2.286 .029

Note: R
2
= .182 for Step1; R
2
= .540 ΔR
2
= .109 for Step 2, p < .029.
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A stepwise multiple linear regression of fcMRI in the vMPFC on participants’
estimated frequencies of thoughts about future events, PCDD and BAQ scores rendered
one model, which included participants’ estimated frequencies of thoughts about future
events (R
2
= .427; Table 4.13).

Table 4.13. Model rendered by stepwise multiple regression of fcMRI in the vMPFC on
participants’ estimated frequencies of thoughts about future events (“thoughts about
future”, for short), and PCDD and BAQ scores.
Model B Std. Error Beta t p
1 Constant .579 2.169

.267 .791
Thoughts
about
future
1.425 .510 .427 2.793 .008
Note: R
2
= .427.
PCC. Participants’ fcMRI in the PCC correlated with the following variables
(Table 4.7): (i) participants’ estimated frequencies of thoughts about their ongoing body
status, (ii) participants’ estimated frequencies of thoughts about their personality traits
and biographic facts; (iii) participants’ Private SCS scores, (iv) participants’ Public SCS
scores, and (v) participants’ Anxiety SCS scores. Three stepwise multiple linear
regression analyses were performed in order to avoid not collinearity between the
independent variables.
A stepwise multiple regression of fcMRI in the PCC on participants’ estimated
frequencies of thoughts regarding one’s going body status events, and Private-SCS and
Anxiety – SCS scores, rendered two models: Model 1, including participants’ Anxiety –
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SCS scores (R
2
= .520); and Model 2, including participants’ Private-SCS and Anxiety –
SCS scores (ΔR
2
= .101, p < .025, Table 4.14).
Table 4.14. Models rendered by stepwise multiple regression of fcMRI in the PCC on
participants’ estimated frequencies of thoughts regarding their going body status events,
Private-SCS scores, and Anxiety – SCS scores.
Model B Std. Error Beta t p
1 Constant 51.757 2.816 18.379 .000
Anxiety -SCS -.739 .205 -.520 -3.605 .001

2 Constant 60.961 4.738 12.866 .000
Anxiety -SCS -.678 .195 -.477 -3.481 .001
Private -SCS -.370 .158 -.321 -2.344 .025

Notes: R
2
= .520, Model 1; ΔR
2
= .101, p < .025 for Model 2.
A stepwise multiple regression of fcMRI in the PCC on participants’ estimated
frequencies of thoughts about their going body status, and Public –SCS scores yielded
one model, which included participants’ Public SCS (R
2
= .408, Table 4.15).
Table 4.15. Model rendered by stepwise multiple regression of fcMRI in the PCC on
participants’ estimated frequencies of thoughts regarding their ongoing body status, and
Public-SCS scores.
Model B Std. Error Beta t p
1 Constant 55.560 5.110 10.872 .000
Public -SCS -.700 .265 -.408 -2.647 .012

Note: R
2
= .408.

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A stepwise multiple regression of fcMRI in the pCC on participants’ estimated
frequencies of thoughts about their traits and facts, Private-SCS scores, and Anxiety –
SCS scores rendered two models: Model 1, including participants’ Anxiety – SCS scores
(R
2
= .520); Model 2, including participants’ Private-SCS and Anxiety – SCS scores (ΔR

2
= .101, p < .025, Table 4.16).
Table 4.16. Models rendered by stepwise multiple regression of fcMRI in the PCC on
participants’ estimated frequencies of thoughts regarding their traits and facts, Private-
SCS scores, and Anxiety – SCS scores
Notes: R
2
= .520 for Model 1; ΔR
2
= .101, for Model 2, p < .025.
Retrosplenial cortex (Rsp, ROI # 5, Table 4.1). Participants’ fcMRI in the left
retrosplenium correlated with their estimated frequencies of thoughts about their ongoing
body status, and estimated frequencies of thoughts about present events. A stepwise
multiple regression of fcMRI in the retrosplenium on these two variables generated a
model that included participants’ estimated frequencies of thoughts about their ongoing
body status (R
2
= .350, Table 4.17).

Model

t p B Std. Error Beta
1 Constant 51.757 2.816

18.379 .000
Anxiety -SCS -.739 .205 -.520 -3.605 .001

2 Constant 60.961 4.738

12.866 .000
Anxiety -SCS -.678 .195 -.477 -3.481 .001
Private -SCS -.370 .158 -.321 -2.344 .025
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Table 4.17. Model rendered by stepwise multiple regression of fcMRI in in the left
retrosplenium and participants’ estimated frequencies of thoughts regarding their ongoing
body status (“thoughts about body” for short) and estimated frequencies of thoughts
regarding present events.

Model B Std. Error Beta t p
1 Constant 25.989 2.462 10.558 .000
Thoughts
about body
-1.481 .669 -.350 -2.213 .033

Note: R
2
= .350.

Temporal Parietal Junction. Participants’ fcMRI in the temporal parietal junction
(ROI #8, Table 4.1) correlated negatively with their estimated frequencies of thoughts
about past events, and PCDD scores (Table 4.7). A stepwise multiple regression of
fcMRI in the temporal parietal junction on those two variables rendered two Models:
Model 1, which included participants’ estimated frequencies of thoughts regarding past
events (R
2
= .351), and Model 2, which included both the variables (ΔR
2
= .129, p < .021)
(Table 4.18).

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Table 4.18. Model rendered by stepwise multiple regression of fcMRI in the temporal
parietal junction on participants’ estimated frequencies of thoughts regarding past events
(“thoughts about past”, for short), and PCDD scores.

Model B Std. Error Beta t p
1 Constant 23.998 2.664 9.008 .000
Thoughts about
past
-1.444 .651 -.351 -2.217 .033

2 Constant 44.235 8.736

5.064 .000
Thoughts about
past
-1.600 .614 -.389 -2.606 .013
PCDD -.377 .156 -.361 -2.417 .021
Notes: R
2
= .351 for Model 1; ΔR
2
= .129, p < .021 for Model 2.
Hippocampal formation. Participants’ fcMRI in the right hippocampus
correlated negatively with their estimated frequencies of thoughts regarding their body
ongoing body status, past events, present events, and future events. Three stepwise
multiple linear regression analyses were performed in order to avoid not collinearity
between the independent variables.
A stepwise multiple regression of fcMRI in the right hippocampus on participants’
estimated frequencies of thoughts regarding their ongoing body status, and estimated
frequencies of thoughts regarding present events rendered a model that included only
participants’ estimated frequencies of thoughts about present events (R
2
= .393, Table
4.19).

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236
Table 4.19. Model rendered by multiple regression of fcMRI in the right hippocampus on
participants’ estimated frequencies of thoughts regarding their one’s body ongoing body
status, and estimated frequencies of thoughts regarding present events (“thoughts about
present”, for short)
Model B Std. Error Beta t p
1 Constant 6.405 1.544 4.147 .000
Thoughts about present -.796 .315 -.393 -2.531 .016
Note: R
2
= .393.
A stepwise multiple regression of fcMRI in the right hippocampus on participants’
estimated frequencies of thoughts regarding their body ongoing body status, and
estimated frequencies of thoughts regarding future events rendered a model that included
only participants’ frequencies of thoughts regarding future events (R
2
= .512, Table 4.20).
Table 4.20. Model rendered by multiple regression of fcMRI in the right hippocampus,
on participants’ estimated frequencies of thoughts regarding their body ongoing body
status, and estimated frequencies of thoughts regarding future events (“Thoughts about
future”, for short)
Model B Std. Error Beta t p
1 Constant 6.516 1.200

5.430 .000
Thoughts about future -.997 .282 -.512 -3.529 .001
Note: R
2
= .512.

A stepwise multiple regression of fcMRI in the right hippocampus on participants’
estimated frequencies of thoughts regarding their ongoing body status, and estimated
frequencies of thoughts regarding past events did not render a statistical significant model.
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237

Insula. Participants’ fcMRI in the left insula correlated positively with their BAQ
scores and negatively with their PAC scores (Table 4.8). A stepwise multiple regression
of fcMRi in the left insula on participants’ BAQ and PAC scores rendered two Models
(Table 4.21): Model 1, including participants’ PAC scores (R
2
= .428); Model 2,
including both variables (ΔR
2
change = .090, p < .048). Although there was a trend of
negative correlation between participants’ PAC and BAQ scores (Table 4.5), collinearity
did not seem to be a problem (VIF = 1.080).
Table 4.21. Model rendered by multiple regression of fcMRI in the left insula on
participants’ BAQ and PAC scores
Model B Std. Error Beta t p
1 Constant 4.724 2.250

2.100 .043
PAC -.142 .051 -.428 -2.800 .008

2 Constant -1.695 3.800

-.446 .658
PAC -.114 .050 -.343 -2.257 .031
BAQ .068 .033 .312 2.051 .048

Notes: R
2
= .428 for Model 1; ΔR
2
= .090 p < .048 for Model 2.

Amygdala. Participants’ fcMRI in the left amygdala correlated negatively with
their estimated frequencies of thoughts about present events, Anxiety-SCS and PD scores,
and positively with their BAQ and GFDD scores (Table 4.8). Two stepwise multiple
linear regression analyses were performed in order to avoid collinearity between the
independent variables.
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238
A stepwise multiple regression of fcMRI in the right amygdala on participants’
BAQ, GFDD, and PD scores rendered a model, which included only BAQ scores (R
2
= .342; Table 4. 22).
Table 4.22. Model rendered by multiple regression of fcMRI in the right amygdala on
participants’ BAQ, GFDD, and PD scores
Model B Std. Error Beta t p
1 Constant .227 .820 .277 .783
BAQ .122 .057 .342 2.156 .038
Note: R
2
= .342

A stepwise multiple regression of fcMRI in the right amygdala on participants’
estimated frequencies of thoughts regarding present events, and GFDD scores rendered
two models: Model 1, which included participants’ estimated frequencies of thoughts
regarding present events (R
2
= .518), and Model 2, which include the two variables (ΔR
2
= .088, p < .038) (Table 4.23).
Table 4.23. Models rendered by stepwise multiple regression of fcMRI in the right
amygdala on participants’ estimated frequencies of thoughts regarding present events
(“thoughts about present”, for short), and GFDD scores.

Model B Std. Error Beta t p
1 Constant .227 .746 .305 .763
Thought on present -1.305 .364 -.518 -3.581 .001

2 Constant .227 .710 .320 .751
Thought on present -1.320 .347 -.524 -3.805 .001
GFDD .169 .078 .297 2.156 .038
Note: R
2
= .518 for Model 1; ΔR
2
= .088 p < .038 for Model 2.

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239
Precentral gyrus. Participants’ fcMRI in the right precentral gyrus correlated
positively with their PCDD scores, and negatively with their estimated frequencies of
thoughts about present events, and Anxiety-SCS scores, and PD scores.
A stepwise multiple regression of fcMRI in the right precentral gyrus on
participants’ estimated frequencies of thoughts regarding present events, and GFDD
scores rendered one model, which included only participants’ estimated frequencies of
thoughts regarding present events (R
2
= .383; Table 4.24)
Table 4.24. Model rendered by multiple regression of fcMRI in the right precentral gyrus
on participants’ estimated frequencies of thoughts regarding present events (“Thoughts
about present”, for short), and GFDD scores
Model B Std. Error Beta t p
1 Constant 2.100 .296

7.091 .000
Thoughts
about present
-.354 .145 -.383 -2.451 .019
Note: R
2
= .383.

Postcentral gyrus. Participants’ fcMRI in the left postcentral gyrus correlated
negatively with their estimated frequencies of thoughts regarding future events, Anxiety-
SCS scores, and Private SCS scores (Table 4.8). A stepwise multiple regression analysis
of fcMRI in the left postcentral gyrus on those three variables correlations rendered a
model including only participants’ estimated frequencies of thoughts regarding future
events (R
2
= .348; Table 4.25).
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240
Table 4.25. Model rendered by multiple regression of fcMRI in the left postcentral gyrus
on participants’ estimated frequencies of thoughts regarding future events (“Thoughts
about future”, for short), Anxiety-SCS scores, and Private SCS scores.
Model B Std. Error Beta t p
1 Constant 4.636 .382 12.135 .000
Thoughts about future -.394 .179 -.348 -2.197 .035
Note: R
2
= .348

Participants’ fcMRI in in the right postcentral gyrus correlated negatively with
their estimated frequencies of thoughts regarding past, present and future events, and with
their Anxiety –SCS scores (Table 4.8). Two stepwise multiple linear regression analyses
were performed in order to avoid collinearity between the independent variables.
A stepwise multiple regression of fcMRI in the right postcentral gyrus, and
participants’ estimated frequencies of thoughts about future events, and Anxiety-SCS
rendered a model that included only participants’ estimated frequencies of thoughts about
future events (R
2
= .348; Table 4.26).
Table 4.26. Model rendered by multiple regression of fcMRI the right postcentral gyrus
on participants’ estimated frequencies of thoughts about future event (“Thoughts about
future”, for short) and Anxiety-SCS scores.
Model B Std. Error Beta t p
1 Constant 4.636 .382

12.135 .000
Thoughts about future -.394 .179 -.348 -2.197 .035
Note: R
2
= .348.

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241
A stepwise multiple regression of fcMRI in the right postcentral gyrus on
participants’ estimated frequencies of thoughts regarding past events, and Anxiety-SCS
scores rendered a model that included only participants’ Anxiety-SCS scores (R
2
= 328;
Table 4.27).
Table 4.27. Model rendered by multiple regression of fcMRI the right postcentral gyrus
on participants’ estimated frequencies of thoughts regarding past events, and Anxiety-
SCS scores
Model B Std. Error Beta t p
1 Constant 4.636 .385 12.041 .000
Anxiety - SCS -.149 .073 -.328 -2.051 .048
R
2
= .328

Discussion
The results of this study support that there is a relationship between brain activity
in the absence of an experimental task and self-related processes. Specifically, the data
showed that individuals’ fcMRI in the DMN correlated with their estimated thoughts
during rest, as well as with their personality in relation to how self-related information
tends to be processed. In addition, participants’ fcMRI in body related regions varied also
with differences across individuals in relation to estimated thoughts during rest and to
personality.
In the paragraphs below, I discuss these findings and their possible relevance to
the understanding of self-related states that are not contingent on a task and the treatment
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of psychiatric and psychological disorders, as well as to the understanding of the meaning
of brain activity during rest.

Functional Intrinsic Connectivity and Spontaneous Thoughts
Participants’ estimated frequency of thoughts about their ongoing body status
correlated negatively with fcMRI in the retrosplenium, and, although not reaching
statistical significance, in the hippocampus. In addition, participants’ estimated frequency
of thoughts regarding present and future events correlated negatively with fcMRI in the
hippocampus. Given the well-established role of the hippocampus and retrosplenium in
memory retrieval (see, for example, Cohen & Eichenbaum, 1993; Valenstein et al., 1987),
these findings may relate to the likely possibility that those classes of thoughts did not
require great level of memory retrieval, and thus did not recruit memory-related regions
to a large extent.
Participants’ estimated frequencies of thoughts about future events correlated
positively with fcMRI in the ventral MPFC. This is consistent with other findings in the
existing literature. For example, it has been shown that the ventral MPFC is more active
for reflection on future aspects of oneself than for refection on present aspects of oneself
(Andrews-Hanna et al., 2010). In addition, it is possible that the involvement of the
ventral MPFC in thoughts regarding future events relates to decision-making processes,
given that there is evidence that this region is involved in decision making. For example,
patients with lesions in the vMPFC show poor choice skills particularly by disregarding
high future losses (e.g., (Bechara, Tranel, & Damasio, 2000).
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Participants’ fcMRI in body-related regions correlated negatively with their
estimated frequencies of thoughts about present and future events. Specifically,
participants’ estimated frequencies of thoughts about present events correlated negatively
with fcMRI in the amygdala and right precentral gyrus; and participants’ estimated
frequencies of thoughts about future events correlated negatively with fcMRI in the left
postcentral gyrus. In addition, fcMRI in the insula correlated negatively with participants’
tendencies to daydream (PAC scores). Altogether, these findings could indicate that
mind wandering, including thoughts about present and future events, does not recruit
body-related regions to a large extent. However, this may well be the case only when
thoughts generated during mind wandering do not elicit strong emotional reactions, as
suggested by other results in this study. For example, participants’ scores for GFDD,
which measures an individual’s tendency to have daydreams of a negative content,
correlated positively with fcMRI in the amygdala and precentral gyrus.
Functional Intrinsic Connectivity and Personality Differences
Participants’ fcMRI in the inferior PMC correlated negatively with participants’
Private-SCS, Public –SCS and Anxiety-SCS scores. Given that inferior PMC has been
shown to be a major hub of the DMN (Hagmann et al., 2008), this suggests a relationship
between functional and anatomical properties of DMN and one’s tendency to scrutinize
oneself. Other findings seem to support this view. For example, it has been shown that
Zen meditation, which tends to drive individuals away from scrutinizing themselves, is
associated with changes of activity in the inferior PMC (Pagnoni, 2012).
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On the other hand, participants’ BAQ scores correlated positively with fcMRI in
body-related regions, namely the insula, amygdala and precentral gyrus. This suggests a
possible relationship between individuals’ tendencies to examine their ongoing body
status, and functional and anatomical properties of body-related brain regions. This is
supported by findings from other studies. For example, compared with healthy people,
patients with fibromyalgia show greater fcMRI in the insula (Napadow, Kim, Clauw, &
Harris, 2012).
Possible relevance to the understanding of self-related mental states that are
not contingent on a task, and the treatment of psychological and psychiatric
disorders
The investigation of neural basis of the self has largely focused on states elicited
by tasks requiring individuals to answer questions about themselves. Nonetheless, not all
self-related mental states are contingent on a task requiring individuals to answer self-
related questions or to process other self-related stimuli. These “non-task dependent”
self-related states” may arise in a relatively spontaneous and unrestricted manner when
individuals are not engaged in any specific task (e.g., during rest in experimental studies).
They may also occur in a relatively intrusive manner while individuals are engaged in a
non-self related task (e.g., watching a movie). Furthermore, some “non-task dependent”
self-related states seem to hold little utility to individuals, and may even interfere with
their well-being and thus be considered pathologic. For example, patients with
hypochondria tend to worry excessively about their ongoing body status, which
frequently impairs the quality of their lives.
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The results of our study suggest a relationship between “non-task dependent” self-
related states and fcMRI in DMN and body-related regions. In other words, individuals
who hold a greater tendency to reflect on self-related domains may have differences in
the functional and anatomical organization of their brains.
In addition, the data seem to suggest a possible dichotomy between thoughts,
personality measures and brain activity directed to body processes, and those that are not
directed to body processes. Specifically:
1. Participants’ estimated frequencies of thoughts that did not focus on their
ongoing body status (i.e., thoughts about traits and facts, past events, present
events and future events) correlated positively with one another. Nonetheless,
participants’ estimated frequencies of thoughts about their ongoing body
status correlated positively only with those for thoughts about traits and facts.
2. Participants’ BAQ scores correlated negatively with their Anxiety-SCS scores.
3. Participants’ fcMRI in body-related regions correlated positively with their
BAQ scores but correlated negatively with their estimated frequency of
thoughts not directed to one’s body (e.g., thoughts about past, present and
future events), Private-SCS scores, Anxiety-SCS scores, and PAC scores.
Looking at these findings under the perspective of the capacity theory for
attention (Kahneman, 1973), it is possible that body-related processes interfere with non-
body related processes in terms of attention. This possibility may have implications to the
treatment of psychological and psychiatric disorders. Accordingly, prompting
individuals to process body-related changes may be an effective approach to distract them
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from non-body related processes. Likewise, prompting individuals to process non-body
related information may, in turn, distract them from body related processes.
More specifically, it is possible that mind wandering and self-related thoughts that
are not directed to one’s body may be effective distractors from body sensations, and thus
can be used in individuals who worry excessively about their body changes (e.g.,
hypochondria) or who suffer from conditions that drive them to process body sensations
more frequently (e.g., chronic pain syndromes). This possibility is consistent with
behavioral data showing that distraction techniques are effective in the management of
pain, either in acute pain syndromes (Fernandez & Turk, 1989) or in chronic pain
syndromes (Johnson, 2005).
Likewise, it is possible that processing body sensations may be an effective
distractor from distressing thoughts related to oneself (e.g., worries about one’s self
image) such as those occurring in depressive disorders. This possibility seems to be in
line with the usage of mediation on particularly body sensations (e.g., breathing) and may
help manage anxiety and depression (Goyal et al., 2014). Likewise, it is consistent with
mindfulness-based techniques, which drive one’s awareness to present-moment
experiences related for example to body sensations (e.g., breathing, eating), help with
anxiety (Miller, Fletcher, & Kabat-Zinn, 1995) and depression (Matousek & Dobkin,
2010).

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Possible relevance to the understanding of brain activity during rest
The results of this study conflict with the unqualified notion that DMN is not
contingent on mental processes during rest and relates solely to functional intrinsic
properties of brain networks. The data are rather are consistent with the proposal that
experimental rest involves varied cognitive processes and thus can be regarded as a “task”
(Buckner, Krienen, & Yeo, 2013).
Nonetheless, the results of this study show that resting state activity, namely
fcMRI, varies with participants’ personality measures. This suggests that fcMRI may be a
correlate of the organization of an individuals’ brain. However, that correlate may not be
necessarily better than connectivity measures derived from brain activity during tasks, as
pointed out by others (Buckner et al., 2013). Moreover, given that fcMRI seems to vary
with mental processes during experimental rest, those processes need to be considered in
order to ascertain the relationship between fcMRI and an individual’s anatomical and
functional brain network.
The results also support the idea that DMN regions do not operate alone. Rather,
DMN regions seem to collaborate with body-related regions when needed, for example,
to process body-related changes (e.g., BAQ scores), as well as to process information that
evokes emotional responses (e.g., GFDD scores).

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Conclusion
This study suggests that brain activity during periods of experimental rest relates
to spontaneous thoughts during those periods, including thoughts that are exclusively
about oneself (e.g., thoughts about one’s ongoing body status) as well as those regarding
oneself in relation to others (e.g.. thoughts about life events). Likewise, data in this study
suggest that functional intrinsic connectivity of DMN and body-related regions varies
with one’s personality in relation to how one tends to process self-related information
(e.g., BAQ) as well as one’s tendency to process information not directly related to
oneself (e.g., PD).
Although findings need to be interpreted carefully given that they derive from a
correlational analyses, they should prompt further discussion in regard to the relationship
between brain activity during rest and self-related states that are not contingent on a task.

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General Discussion

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A large part of the investigation of neural underpinnings of self processes has frequently
regarded the self as a single and indivisible entity, and has thus compared processing self-related
stimuli with processing stimuli related to another person, object or animal in the hope to unravel
the behavioral and neural correlates of the self. In this thesis, I sought to investigate the self as a
result of mental states, and to demonstrate that those self-related states are not a single or a
uniform entity that is either present or not in one’s mind, but they rather vary depending on
different factors.
I believe that the data presented in this thesis may prompt discussion about the neural
basis for self-related states, and the differences between self-related and other-related processes
in terms of behavioral and neural correlates

The complex neural underpinnings of self-related states
The results presented here demonstrated that self-related states focusing on an
individual’s ongoing status (i.e., core self) are different from those that focus on historical
aspects of an individual’s biography and identify (i.e., autobiographical self). Specifically, core
self states are associated with greater activity in body related regions (e.g., insula) than
autobiographical-self states; in turn, autobiographical-self states are associated with greater
activity in memory related regions (e.g., hippocampus) than core self states.
Still, as the data support, memories accessed during autobiographical self states are
treated as “objects” by the brain, and may elicit emotional responses and generate a core self
state (Damasio, 2000). Likewise, processing certain body sensations during core self states may
prompt an individual to retrieve autobiographical memories and thus drive one’s mind to an
autobiographical state.
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Moreover, autobiographical self states vary depending on the domain of historical aspects
being processed. For example, personality traits tend to be associated with a certain emotional
value, and to depend on a subjective judgment of one’s memories regarding a given trait,
whereas biographic facts tend to be more objective as they are incontrovertible and easily
verifiable. Probably for this reason, in my study, personality traits yielded a greater level of
activity in regions involved emotion-related somatic representations, such as the insular cortices,
than biographic facts. In addition, because biographic facts tend to be more relevant to one’s
daily life and identity than traits, processing biographic facts tends to elicit greater memory
retrieval, and related brain activity (e.g., hippocampus) than traits. Likewise, the results support
that core self states vary depending on the body changes being processed. Processing
interoceptive body changes is different from processing exteroceptive body changes, in terms of
brain activity generated in body-related regions and cortical midline regions, as well as regions
specifically dedicated to memory processes.
In addition, the tasks used in the studies investigating the self are generally the same for
all participants, but the participants are likely to vary in relation to how they perform those tasks.
For example, some individuals may regard a certain biographic datum as objective and
incontrovertible, whereas different individuals may regard that same datum as subjective and
uncertain. Likewise, some individuals may regard a given body change as inconsequential, but
other individuals may consider that change unsettling. As the results demonstrate, behavioral
(i.e., reaction times to the questions) and neural correlates of autobiographical self and core self
states vary depending on differences across individuals in relation to the specific information
being evaluated as well as in relation to one’s personality (i.e., how one tends to process self
related information).
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The differences between individuals are also important to understand self-related states
that are not prompted by a specific self-related question, but instead occur in a more unrestricted,
and at times apparently spontaneous, manner. The work I presented here seems to suggest that
those states depend on the functional and anatomical organization of an individual’s brain,
including hubs of the so-called default mode network, and body-related regions.

Differences of neural correlates between self and other
Individuals’ knowledge regarding their own biographies and their acquaintances’
biographies seems to be acquired in similar manners. Individuals know themselves in relation a
given biographic domain through relevant events experienced and facts learned during their lives.
Likewise, individuals know their acquaintances in relation to a given biographic domain through
relevant events experienced and facts learned during their acquaintanceship.
Nonetheless, there are inexorable differences between oneself and another person,
stemming, for example, from the fact that individuals do not share the same body or the same life
experiences. Whereas individuals are frequently experiencing events related to themselves, they
only experience events relate to their acquaintances when they interact with them. Those
interactions may be limited and uninteresting when they pertain to a distant acquaintance, but
may be very frequent and relevant when they pertain to a close friend or relative. Accordingly,
the difference between self and other depends on who the other is in relation to self.
The meta-analysis of the published studies comparing self and other in relation to domain
of personality traits demonstrated that MPFC is generally more active for self than for other,
possibly because of the greater emotional processing associated with self-related information. On
the other hand, the PMC was more active for other, possibly because of the greater effort in
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memory retrieval required for other. Despite existing literature (e.g., Ochsner et al., 2005) that
suggests that differences of activity in the MPFC depend on the relationship between self and
other, this meta-analyses fail to show differences in that regard.
In addition, the results of the fMRI study reported here demonstrated that the PMC
showed greater activity for other not only in relation to personality traits (as demonstrated in the
meta-analysis) but also to biographic facts. Moreover, brain activity generated for other varied
across individuals in relation to the specific information targeted by the questions (e.g., how
important that information is to the participant’s image of the acquaintance), as well as in
relation to how individual tends to process other-related information (e.g., the degree in which
individuals take other person’s perspective).
Altogether, these findings suggest that the differences between self and other vary
depending on the domain of information in question, on who the other is in relation to self, and
on personality differences in relation to how one tends to process information that pertains to
other.

Conclusion
The evidence does not support that self is a single or indivisible entity that depends
mostly or firstly on a specific brain structure. The self can be rather regarded as a set of mental
states that are constructed with the support of varied brain structures.

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References
Damasio, A. R. (1989). Time-locked multiregional retroactivation: a systems-level proposal for
the neural substrates of recall and recognition. Cognition, 33(1-2), 25–62.
Damasio, A. R. (2000). The Feeling of what Happens. Harcourt Inc.
Ochsner, K. N., Beer, J. S., Robertson, E. R., Cooper, J. C., Gabrieli, J. D. E., Kihsltrom, J. F., &
D'Esposito, M. (2005). The neural correlates of direct and reflected self-knowledge.
NeuroImage, 28(4), 797–814. doi:10.1016/j.neuroimage.2005.06.069

Asset Metadata

Creator Araujo, Helder Filipe Cruz (author)

Core Title Behavioral and neural correlates of core-self and autobiographical-self processes

Contributor Electronically uploaded by the author (provenance)

School College of Letters, Arts and Sciences

Degree Doctor of Philosophy

Degree Program Neuroscience

Publication Date 07/10/2016

Defense Date 05/20/2014

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag autobiographical self,core self,neural correlates,OAI-PMH Harvest,reaction time,self

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Language English

Advisor Damasio, Antonio (committee chair), Chui, Helena (committee member), Damasio, Hanna (committee member), Immordino-Yang, Mary Helen (committee member)

Creator Email haraujo@usc.edu,helderpe@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-436636

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Abstract (if available)

Abstract At a given conscious moment, an individuals’ mind may be allocated to states focusing on self‐related processes. Those states tend to involve retrieving and processing historical aspects of oneself, such as memories for events and facts pertaining to one’s autobiography (states that have been designated as “autobiographical self”, Damasio, 1998), or examining one’s ongoing body status, such as sensations pertaining to one’s internal milieu (states that have been designated as “core self”, Damasio, 1998). ❧ In addition, self‐related mental states may be elicited by specific stimuli directing an individual to process certain self-related information, such as questions used as stimuli in research studies